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Python Tutorial: CSV Module - How to Read, Parse, and Write CSV Files
 
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In this Python Programming Tutorial, we will be learning how to work with csv files using the csv module. We will learn how to read, parse, and write to csv files. CSV stands for "Comma-Separated Values". It is a common format for storing information. Knowing how to read, parse, and write this information to files will open the door to working with a lot of data throughout the world. Let's get started. The code from this video can be found at: https://github.com/CoreyMSchafer/code_snippets/tree/master/Python-CSV ✅ Support My Channel Through Patreon: https://www.patreon.com/coreyms ✅ Become a Channel Member: https://www.youtube.com/channel/UCCezIgC97PvUuR4_gbFUs5g/join ✅ One-Time Contribution Through PayPal: https://goo.gl/649HFY ✅ Cryptocurrency Donations: Bitcoin Wallet - 3MPH8oY2EAgbLVy7RBMinwcBntggi7qeG3 Ethereum Wallet - 0x151649418616068fB46C3598083817101d3bCD33 Litecoin Wallet - MPvEBY5fxGkmPQgocfJbxP6EmTo5UUXMot ✅ Corey's Public Amazon Wishlist http://a.co/inIyro1 ✅ Equipment I Use and Books I Recommend: https://www.amazon.com/shop/coreyschafer ▶️ You Can Find Me On: My Website - http://coreyms.com/ My Second Channel - https://www.youtube.com/c/coreymschafer Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Instagram - https://www.instagram.com/coreymschafer/ #Python
Views: 285355 Corey Schafer
Learn Python - Full Course for Beginners [Tutorial]
 
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This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you'll be a python programmer in no time! ⭐️ Contents ⭐ ⌨️ (0:00) Introduction ⌨️ (1:45) Installing Python & PyCharm ⌨️ (6:40) Setup & Hello World ⌨️ (10:23) Drawing a Shape ⌨️ (15:06) Variables & Data Types ⌨️ (27:03) Working With Strings ⌨️ (38:18) Working With Numbers ⌨️ (48:26) Getting Input From Users ⌨️ (52:37) Building a Basic Calculator ⌨️ (58:27) Mad Libs Game ⌨️ (1:03:10) Lists ⌨️ (1:10:44) List Functions ⌨️ (1:18:57) Tuples ⌨️ (1:24:15) Functions ⌨️ (1:34:11) Return Statement ⌨️ (1:40:06) If Statements ⌨️ (1:54:07) If Statements & Comparisons ⌨️ (2:00:37) Building a better Calculator ⌨️ (2:07:17) Dictionaries ⌨️ (2:14:13) While Loop ⌨️ (2:20:21) Building a Guessing Game ⌨️ (2:32:44) For Loops ⌨️ (2:41:20) Exponent Function ⌨️ (2:47:13) 2D Lists & Nested Loops ⌨️ (2:52:41) Building a Translator ⌨️ (3:00:18) Comments ⌨️ (3:04:17) Try / Except ⌨️ (3:12:41) Reading Files ⌨️ (3:21:26) Writing to Files ⌨️ (3:28:13) Modules & Pip ⌨️ (3:43:56) Classes & Objects ⌨️ (3:57:37) Building a Multiple Choice Quiz ⌨️ (4:08:28) Object Functions ⌨️ (4:12:37) Inheritance ⌨️ (4:20:43) Python Interpreter Course developed by Mike Dane. Check out his YouTube channel for more great programming courses: https://www.youtube.com/channel/UCvmINlrza7JHB1zkIOuXEbw 🐦Follow Mike on Twitter - https://twitter.com/mike_dane 🔗If you liked this video, Mike accepts donations on his website: https://www.mikedane.com/contribute/ ⭐️Other full courses by Mike Dane on our channel ⭐️ 💻C: https://youtu.be/KJgsSFOSQv0 💻C++: https://youtu.be/vLnPwxZdW4Y 💻SQL: https://youtu.be/HXV3zeQKqGY 💻Ruby: https://youtu.be/t_ispmWmdjY 💻PHP: https://youtu.be/OK_JCtrrv-c 💻C#: https://youtu.be/GhQdlIFylQ8 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Views: 7388842 freeCodeCamp.org
Python for Beginners with Spyder IDE
 
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This introduction includes information about naming variables, built-in constants, reserved keywords, built-in functions, syntax highlighting, data types (integer, float, list, tuple, dictionary), and basic commands to built a first program. See http://apmonitor.com/che263/index.php/Main/PythonBasics for example code.
Views: 28855 APMonitor.com
Intro and Getting Stock Price Data - Python Programming for Finance p.1
 
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Welcome to a Python for Finance tutorial series. In this series, we're going to run through the basics of importing financial (stock) data into Python using the Pandas framework. From here, we'll manipulate the data and attempt to come up with some sort of system for investing in companies, apply some machine learning, even some deep learning, and then learn how to back-test a strategy. I assume you know the fundamentals of Python. If you're not sure if that's you, click the fundamentals link, look at some of the topics in the series, and make a judgement call. If at any point you are stuck in this series or confused on a topic or concept, feel free to ask for help and I will do my best to help. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 361611 sentdex
Natural Language Processing Apps with Tkinter [NLPiffy GUI]
 
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Natural Language Processing Apps with Tkinter [NLPiffy GUI] In this tutorial we will be building another NLP based Application with python tkinter. We will learn how to do sentiment analysis,entity extraction,tokenization and many more with Spacy,TextBlob. Code:https://github.com/Jcharis/NLPiffy Check out the Free Course on- Learn Julia Fundamentals http://bit.ly/2QLiLG8 If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech ==Get The Data Science Prime App== @ Playstore : http://bit.ly/2LArYQu Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
New Python Tutorial: Diagnose data for cleaning
 
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First video of our latest course by Daniel Chen: Cleaning Data in Python. Like and comment if you enjoyed the video! A vital component of data science involves acquiring raw data and getting it into a form ready for analysis. In fact, it is commonly said that data scientists spend 80% of their time cleaning and manipulating data, and only 20% of their time actually analyzing it. This course will equip you with all the skills you need to clean your data in Python, from learning how to diagnose your data for problems to dealing with missing values and outliers. At the end of the course, you'll apply all of the techniques you've learned to a case study in which you'll clean a real-world Gapminder dataset! So you've just got a brand new dataset and are itching to start exploring it. But where do you begin, and how can you be sure your dataset is clean? This chapter will introduce you to the world of data cleaning in Python! You'll learn how to explore your data with an eye for diagnosing issues such as outliers, missing values, and duplicate rows. Try the first chapter for free: https://www.datacamp.com/courses/cleaning-data-in-python
Views: 16762 DataCamp
14 讀取外部檔案與切割到串列
 
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文大Python程式入門或證照第5次PYTHON轉VBA&改為Cells物件與事件驅動和除錯&自訂表單&啟動表單程式撰寫隨活頁簿啟動&範例BMI改用VB&MONTHCAI改為VBA版本&串列型態與輸入成績練習&讀取外部檔案與切割到串列&讀取檔案與計算成績 上課內容: 01_重點回顧與PYTHON轉VBA 02_PYTHON轉VBA細節說明 03_將輸入輸出改為Cells物件與事件驅動和除錯 04_將輸入輸出改為自訂表單 05_自訂表單加入元件設計說明 06_自訂表單程式撰寫與ENTER轉為按鈕 07_啟動表單程式撰寫隨活頁簿啟動 08_範例BMI改用VBA說明 09_用Range物件取得值與表單設計 10_九九乘法表改用VBA輸出 11_MONTHCAI改為VBA版本 12_串列型態與輸入成績練習 13_串列型態與計算總分與平均 14_讀取外部檔案與切割到串列 15_讀取檔案與計算成績 完整影音 http://goo.gl/aQTMFS 教學論壇(之後課程會放論壇上課學員請自行加入): https://groups.google.com/forum/#!forum/pccu_python_2018_2 懶人包: EXCEL函數與VBA http://terry28853669.pixnet.net/blog/category/list/1384521 EXCEL VBA自動化教學 http://terry28853669.pixnet.net/blog/category/list/1384524 TQC+Python證照目錄: Python 第1類:基本程式設計 技能內容:變數與常數、指定敘述、標準輸入輸出、運算式、算術運算子、數學函式的應用、格式化的輸出Python 第2類:選擇敘述 技能內容:if、if...else、if…elif Python 第3類:迴圈敘述 技能內容:while、for…in Python 第4類:進階控制流程 技能內容:常用的控制結構、條件判斷、迴圈 Python 第5類:函式(Function) 技能內容:函式使用、傳遞參數、回傳資料、內建函式、區域變數與全域變數 Python 第6類:串列(List)的運作(一維、二維以及多維) 技能內容:串列的建立、串列的函式、串列參數傳遞、串列應用 Python 第7類:數組(Tuple)、集合(Set)以及詞典(Dictionary) 技能內容:數組、集合、詞典的建立、運作及應用 Python 第8類:字串(String)的運作 技能內容:字串的建立、字串的庫存函式、字串的應用 Python 第9類:檔案與異常處理 技能內容:文字I/O、檔案的建立、寫入資料與讀取資料、二進位I/O、編碼(Encoding)、異常處理 課程簡介:入門 建置Python開發環境 基本語法與結構控制 迴圈、資料結構及函式 VBA重要函數到Python 檔案處理 資料庫處理 課程簡介:進階 網頁資料擷取與分析、Python網頁測試自動化、YouTube影片下載器 處理 Excel 試算表、處理 PDF 與 Word 文件、處理 CSV 檔和 JSON 資料 實戰:PM2.5即時監測顯示器、Email 和文字簡訊、處理影像圖片、以 GUI 自動化來控制鍵盤和滑鼠 上課用書: 參考書目 Python初學特訓班(附250分鐘影音教學/範例程式) 作者: 鄧文淵/總監製, 文淵閣工作室/編著 出版社:碁峰? 出版日期:2016/11/29 吳老師 107/12/3 EXCEL,VBA,Python,文化推廣部,EXCEL,VBA,函數,程式設計,線上教學,PYTHON安裝環境
Python For Data Science Tutorial 3 (in Urdu)
 
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Watch it at 480p (or higher) screen resolution. This tutorial includes: 1. Tuples and Random Number Generation in Python 2. Pie-chart, Bar chart and histogram creation using matplotlib 3. Accessing data in structured flat-file form (text files, csv files and excel files covered in this tutorial) Relevant data set files and ppt slides for this tutorial may be downloaded from: https://sites.google.com/site/drraheelsiddiqi/teaching/python-for-data-science
Views: 287 Raheel Siddiqi
How to extract text from an image in python | pytesseract | Image to text processing
 
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In this tutorial, we shall demonstrate you how to extract texts from any image in python. So we shall write a program in python using the module pytesseract that will extract text from any image like .jpg, .jpeg, .png etc. Please subscribe to my youtube channel for such tutorials Watch the same tutorial on how to extract text from an image in Linux below: https://youtu.be/gLUQ8uaaw8A Please watch the split a file by line number here: https://youtu.be/ADRmbu3puCg Split utility in Linux/Unix : to break huge file into small pieces https://www.youtube.com/watch?v=ADRmbu3puCg How to keep sessions alive in terminal/putty infinitely in linux/unix : Useful tips https://www.youtube.com/watch?v=ARIgHdpxaU8 Random value generator and shuffling in python https://www.youtube.com/watch?v=AKwnQQ8TBBM Intro to class in python https://www.youtube.com/watch?v=E6kKZXHS5hM Lists, tuples, dictionary in python https://www.youtube.com/watch?v=Axea1CSewzc Python basic tutorial for beginners https://www.youtube.com/watch?v=_JyjbZc0euY Python basics tutorial for beginners part 2 -variables in python https://www.youtube.com/watch?v=ZlsptvP69NU Vi editor basic to advance part 1 https://www.youtube.com/watch?v=vqxQx-NNyFM Vi editor basic to advance part 2 https://www.youtube.com/watch?v=OWKp2DLaFyY Keyboard remapping in linux, switching keys as per your own choice https://www.youtube.com/watch?v=kJz7uKDyZjs How to install/open an on sceen keyboard in Linux/Unix system https://www.youtube.com/watch?v=d71i9SZX6ck Python IDE for windows , linux and mac OS https://www.youtube.com/watch?v=-tG54yoDs68 How to record screen or sessions in Linux/Unix https://www.youtube.com/watch?v=cx59c15-c8s How to download and install PAGE GUI builder for python https://www.youtube.com/watch?v=dim725Px2hM Create a basic Login page in python using GUI builder PAGE https://www.youtube.com/watch?v=oCAWWUhwEUQ Working with RadioButton in python in PAGE builder https://www.youtube.com/watch?v=YJbQvpzJDr4 Basic program on Multithreading in python using thread module https://www.youtube.com/watch?v=RGm3989ekAc
Views: 33601 LinuxUnixAix
Data Science Tutorial | Data Science for Beginners | Data Science with Python Tutorial | Simplilearn
 
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This Data Science Tutorial will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist. This Data Science tutorial will cover the following topics: 1. What is Data Science? ( 00:43 ) 2. Who is a Data Scientist? ( 02:02 ) 3. What does a Data Scientist do? ( 02:25 ) To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the slides here: https://goo.gl/V4Zn8i Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-bTTxei-Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 43344 Simplilearn
How to Sort CSV files and lists in Python
 
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This is a tutorial concerning how to sort CSV files and lists easily within python by column. The logic possibly by programming plus the simplicity of being able to sort columns makes python a superb choice for managing CSV documents and lists that are delimited by something. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 52672 sentdex
Python Tutorial for Beginners [Full Course] 2019
 
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Watch this Python tutorial to learn Python programming for machine learning and web development. 🔥Get My Complete Python Programming Course with a 90% Discount (LIMITED to the first 200 students): https://goo.gl/P64rZ8 📕Get My FREE Python Cheat Sheet: http://bit.ly/2Gp80s6 👍Subscribe for more Python tutorials like this: https://goo.gl/6PYaGF #Python, #MachineLearning, #WebDevelopment 🔗Supplementary Materials (Spreadsheet): https://goo.gl/x77mLc 📔Python Exercises for Beginners https://goo.gl/1XnQB1 ⭐My Favorite Python Books - Python Crash Course: https://amzn.to/2GqMdjG - Automate the Boring Stuff with Python: https://amzn.to/2N71d6S - A Smarter Way to Learn Python: https://amzn.to/2UZa6lE - Machine Learning for Absolute Beginners: https://amzn.to/2Gs0koL - Hands-on Machine Learning with scikit-learn and TensorFlow: https://amzn.to/2IdUuJy TABLE OF CONTENT 00:00:00 Introduction 00:01:49 Installing Python 3 00:06:10 Your First Python Program 00:08:11 How Python Code Gets Executed 00:11:24 How Long It Takes To Learn Python 00:13:03 Variables 00:18:21 Receiving Input 00:22:16 Python Cheat Sheet 00:22:46 Type Conversion 00:29:31 Strings 00:37:36 Formatted Strings 00:40:50 String Methods 00:48:33 Arithmetic Operations 00:51:33 Operator Precedence 00:55:04 Math Functions 00:58:17 If Statements 01:06:32 Logical Operators 01:11:25 Comparison Operators 01:16:17 Weight Converter Program 01:20:43 While Loops 01:24:07 Building a Guessing Game 01:30:51 Building the Car Game 01:41:48 For Loops 01:47:46 Nested Loops 01:55:50 Lists 02:01:45 2D Lists 02:05:11 My Complete Python Course 02:06:00 List Methods 02:13:25 Tuples 02:15:34 Unpacking 02:18:21 Dictionaries 02:26:21 Emoji Converter 02:30:31 Functions 02:35:21 Parameters 02:39:24 Keyword Arguments 02:44:45 Return Statement 02:48:55 Creating a Reusable Function 02:53:42 Exceptions 02:59:14 Comments 03:01:46 Classes 03:07:46 Constructors 03:14:41 Inheritance 03:19:33 Modules 03:30:12 Packages 03:36:22 Generating Random Values 03:44:37 Working with Directories 03:50:47 Pypi and Pip 03:55:34 Project 1: Automation with Python 04:10:22 Project 2: Machine Learning with Python 04:58:37 Project 3: Building a Website with Django Stay in Touch: https://www.facebook.com/programmingwithmosh/ https://twitter.com/moshhamedani http://programmingwithmosh.com
Views: 3098931 Programming with Mosh
FOREX Harmonic Pattern Scanning Algorithm in Python pt. 2: Pattern Finding
 
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In this installation of the Harmonic Pattern Scanning Algorithm for FOREX, we will eliminate the look-forward bias from the peak detection function and build the basic pattern recognition ability of the program. Harmonic patterns have an up-down-up-down (or the reverse) basic pattern. In this video, we search the time series space for sequences of local extrema that exhibit this basic pattern. In the next video we will tackle the exact fibonacci retracement levels that need to be met for harmonic patterns to become evident in the dataset. As always, thanks for watching!
Views: 4517 PythonParseltongue
Python: List index out of range
 
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Discusses how to debug the list index out of range error based on some examples
Views: 11102 LearningNinja
Natural language processing using AWS | Amazon comprehend | Detect language/Sentiment from Text
 
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In this tutorial, we shall learn how to use this AWS service called Comprehend to process natural unstructured text. We can detect the sentiment from the text We can detect the language from any text We can detect key-phrase and other entities from the text or a paragraph using this service. Please subscribe to my youtube channel for such tutorials Please watch the split a file by line number here: https://youtu.be/ADRmbu3puCg Split utility in Linux/Unix : to break huge file into small pieces https://www.youtube.com/watch?v=ADRmbu3puCg How to keep sessions alive in terminal/putty infinitely in linux/unix : Useful tips https://www.youtube.com/watch?v=ARIgHdpxaU8 Random value generator and shuffling in python https://www.youtube.com/watch?v=AKwnQQ8TBBM Intro to class in python https://www.youtube.com/watch?v=E6kKZXHS5hM Lists, tuples, dictionary in python https://www.youtube.com/watch?v=Axea1CSewzc Python basic tutorial for beginners https://www.youtube.com/watch?v=_JyjbZc0euY Python basics tutorial for beginners part 2 -variables in python https://www.youtube.com/watch?v=ZlsptvP69NU Vi editor basic to advance part 1 https://www.youtube.com/watch?v=vqxQx-NNyFM Vi editor basic to advance part 2 https://www.youtube.com/watch?v=OWKp2DLaFyY Keyboard remapping in linux, switching keys as per your own choice https://www.youtube.com/watch?v=kJz7uKDyZjs How to install/open an on sceen keyboard in Linux/Unix system https://www.youtube.com/watch?v=d71i9SZX6ck Python IDE for windows , linux and mac OS https://www.youtube.com/watch?v=-tG54yoDs68 How to record screen or sessions in Linux/Unix https://www.youtube.com/watch?v=cx59c15-c8s How to download and install PAGE GUI builder for python https://www.youtube.com/watch?v=dim725Px2hM Create a basic Login page in python using GUI builder PAGE https://www.youtube.com/watch?v=oCAWWUhwEUQ Working with RadioButton in python in PAGE builder https://www.youtube.com/watch?v=YJbQvpzJDr4 Basic program on Multithreading in python using thread module https://www.youtube.com/watch?v=RGm3989ekAc
Views: 263 LinuxUnixAix
Data Science In 5 Minutes | Data Science For Beginners | What Is Data Science? | Simplilearn
 
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This Data Science tutorial video will give you an idea on the life of a Data Scientist, steps involved in Data science project, roles & salary offered to a Data Scientist. Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple terms, it is the umbrella of techniques used when trying to extract insights and information from data. Now, let us get started and understand what is Data Science all about. Below topics are explained in this Data Science tutorial: 1. Life of a Data Scientist 2. Steps in Data Science project - Understanding the business problem - Data acquisition - Data preparation - Exploratory data analysis - Data modeling - Visualization and communication - Deploy & maintenance 3. Roles offered to a Data Scientist 4. Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-X3paOmcrTjQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 416159 Simplilearn
Weka Tutorial 02: Data Preprocessing 101 (Data Preprocessing)
 
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This tutorial demonstrates various preprocessing options in Weka. However, details about data preprocessing will be covered in the upcoming tutorials.
Views: 176790 Rushdi Shams
Naïve Bayes Classifier -  Fun and Easy Machine Learning
 
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Naive Bayes Classifier- Fun and Easy Machine Learning ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS COURSE - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML ►MACHINE LEARNING COURSES - http://augmentedstartups.info/machine-learning-courses -------------------------------------------------------------------------------- Now Naïve Bayes is based on Bayes Theorem also known as conditional Theorem, which you can think of it as an evidence theorem or trust theorem. So basically how much can you trust the evidence that is coming in, and it’s a formula that describes how much you should believe the evidence that you are being presented with. An example would be a dog barking in the middle of the night. If the dog always barks for no good reason, you would become desensitized to it and not go check if anything is wrong, this is known as false positives. However if the dog barks only whenever someone enters your premises, you’d be more likely to act on the alert and trust or rely on the evidence from the dog. So Bayes theorem is a mathematic formula for how much you should trust evidence. So lets take a look deeper at the formula, • We can start of with the Prior Probability which describes the degree to which we believe the model accurately describes reality based on all of our prior information, So how probable was our hypothesis before observing the evidence. • Here we have the likelihood which describes how well the model predicts the data. This is term over here is the normalizing constant, the constant that makes the posterior density integrate to one. Like we seen over here. • And finally the output that we want is the posterior probability which represents the degree to which we believe a given model accurately describes the situation given the available data and all of our prior information. So how probable is our hypothesis given the observed evidence. So with our example above. We can view the probability that we play golf given it is sunny = the probability that we play golf given a yes times the probability it being sunny divided by probability of a yes. This uses the golf example to explain Naive Bayes. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 185037 Augmented Startups
Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka Python tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) gives an introduction to Machine Learning and how to implement machine learning algorithms in Python. Below are the topics covered in this tutorial: 1. Why Machine Learning? 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. KNN algorithm 6. Unsupervised Learning 7. K-means Clustering Algorithm Check out our playlist for more videos: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 161987 edureka!
100 COOL THINGS IN PYTHON (PART 1) - CS50 on Twitch, EP. 14
 
03:14:03
Join CS50's head course assistant, Veronica Nutting, for a tour of some of Python's cool features (with an eventual goal of reaching 100 over several parts!), from data structures to analyzing presidential data. Co-hosted by Colton Ogden. Join us live at twitch.tv/cs50tv and be a part of the live chat every week. This is CS50 on Twitch.
Views: 5678 CS50
How to read Excel files with Python (xlrd tutorial)
 
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Learn how to read out data from an Excel document using the xlrd Python module. The xlsx and xls file formats are supported. xlrd docs: http://www.lexicon.net/sjmachin/xlrd.html Type Numbers: 0 - XL_CELL_EMPTY 1 - XL_CELL_TEXT 2 - XL_CELL_NUMBER 3 - XL_CELL_DATE 4 - XL_CELL_BOOLEAN 5 - XL_CELL_ERROR 6 - XL_CELL_BLANK
Views: 208645 triforcelink
Learn Python in Hindi - Data Types
 
25:22
in this video we will understand Python Data types in Hindi. what is String in python what is integer in python what is float in python what is list in python what is tuple in python what is Dictionary in python Copyright © 2014 by Rajiv Sharma ([email protected]) All Rights Reserved. VFXPipeline YouTube Channel and its content is copyright of Rajiv Sharma. Any redistribution or reproduction of part or all of the contents in any form is prohibited other than the following: 1.you can not remove starting 3 second vfxpipeline intro 2.you can not re-upload vfxpipeline channel videos on YouTube or any other website. 3.you can share the links of vfxpipeline channel videos. 4.you can download and share with others for Free. 5.All Free Content : you can not sell vfxpipeline channel videos
Views: 16608 VFX Pipeline
Python Skill: What is Pseudocode?
 
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This video explains why writing pseudocode matters. It begins to outline a text-based adventure game you should try writing in Python. Use your creativity!!!
Views: 31 Robyn Allen
Python 3 Programming Tutorial - Reading from a CSV spreadsheet
 
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In this Python 3 programming tutorial, we cover how to read data in from a CSV spreadsheet file. CSV, literally standing for comma separated variable, is just a file that has data that is separated by some sort of delimiter, it does not have to be a comma. Luckily for us, Python 3 has a built in module for reading and writing from and to CSV files! Sample code for this basics series: http://pythonprogramming.net/beginner-python-programming-tutorials/ Python 3 Programming tutorial Playlist: http://www.youtube.com/watch?v=oVp1vrfL_w4&feature=share&list=PLQVvvaa0QuDe8XSftW-RAxdo6OmaeL85M http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 238722 sentdex
Data Mining Lecture -- Bayesian Classification | Naive Bayes Classifier | Solved Example (Eng-Hindi)
 
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In the bayesian classification The final ans doesn't matter in the calculation Because there is no need of value for the decision you have to simply identify which one is greater and therefore you can find the final result. -~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 217749 Well Academy
Tutoriel Python -  Les fichiers #9
 
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Dans ce 9ème tutoriel pour apprendre à programmer en Python, découvrons comment manipuler les fichiers. Les vidéos de la série : - #1 : Les entrées sorties variables https://www.youtube.com/watch?v=PVB8Qn5bjqY - #2 : Les conditions et booléens https://www.youtube.com/watch?v=tWXSI0qN_To - #3 : Les listes https://www.youtube.com/watch?v=Kwxdlu2JB9w - #4 : Les boucles https://www.youtube.com/watch?v=rrWQ7s2hTFg - #5 : Deviner le nombre (exercice) https://www.youtube.com/watch?v=e9JJsfGLk2w - #6 : Les fonctions https://www.youtube.com/watch?v=WRm6_yLtseQ - #7 : Les modules https://www.youtube.com/watch?v=qqZEpqHM7UQ - #8 : Les structures de données (tuples, dictionnaires...) https://www.youtube.com/watch?v=5ZsPMfnlk5A - #9 : Les fichiers https://www.youtube.com/watch?v=mq1KqzmbEMs - #10 : Analyse démographique (exercice) https://www.youtube.com/watch?v=CtLThUDOzhA Quelques liens : - mon site internet : http://www.lucaswillems.com - mon twitter : http://twitter.com/lcswillems
Views: 29835 Lucas Willems
Python Loops Tutorial | Python For Loop | While Loop Python | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka "Python Loops" tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) will help you in understanding different types of loops used in Python. You will be learning how to implement all the loops in python practically. Check out our playlist for more videos: https://goo.gl/Na1p9G Below are the topics covered in this tutorial: 1) Why to use loops? 2) What are loops 3) Types of loops in Python: While, For, Nested 4) Demo on each Python loop Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #Pythontutorial #Pythononlinetraining #Pythonforbeginners #Pythonloops How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working." For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 67636 edureka!
Python Basics Part 11 (Regular Expressions) - Jose Portilla
 
18:57
Explore the full course on Udemy (special discount included in the link): https://www.udemy.com/draft/1337374/?couponCode=PYYOUTUBENARRATIVE This course is designed to take you from a complete beginner in programming all the way to becoming an effective programmer that can use Python to solve real tasks! I am Jose Portilla and I am the most popular Python instructor on the Udemy platform. I have taught Python programming at Fortune 500 companies and I am very excited to bring the same quality of material to Udemy! Python is used by some of the world largest companies to accomplish all kinds of tasks. This course is also completely different than any other course on Udemy, it incorporates a narrative story that helps engage students and also provides context to the different tasks you have to accomplish. We utilize project based learning to effectively teach Python and give you the skills to put Python on your resume. We have numerous projects and tasks for you to practice what you are learning. In addition to this we have Question and Answer forums where Teaching Assistants and myself are present to help answer any questions you may have, we also have a chat channel where you can talk to other students to team up on your own projects! We will cover a lot of topics in this course! Including: Basic Python Data Types such as numbers, variables, lists, dictionaries, tuples, sets, and more. Key Control Flow - This is the logic that helps run your code, such as if, elif, and else statements. Loops - We'll show you how to become an expert user of for loops and while loops so you can effectively program. Functions - You will learn how to create clean, reusable functions that help automate tasks that you repeat. Object Oriented Programming (OOP) - We will explain OOP in a clear and steady way, helping you master one of Python's most powerful features. Web Scraping - Learn to use the BeautifulSoup and Requests libraries to perform web scraping. CSV Files - You'll be able to use Python's built in csv library to work with csv data with Python. PDF Files - Learn about the PyPDF2 library that allows you to read PDF files pro grammatically. Zip Files - See how Python can zip files and extract information from already compressed zip files. OS Module - Discover how to perform operating system level commands with Python's os module. Images - You will learn how to edit and resize images with Python. Decryption and Encryption - See how to use the cryptography library with Python to encode and decode encrypted messages. Geographical Mapping - We'll show you how to use Python in conjunction with the Google Map's API to plot information on a map! and so much more!
Views: 706 Udemy Tech
Python basic level || Python as calculator || Data science beginners || RR ITEC
 
09:03
(Data Science Training - https://www.datahexa.com/data-science ) This datahexa Data Science course video (Data Science Blog Series: http://rritec.blogspot.com/p/datascience-with-r.html) will take you through the need of data science, what is data science, data science use cases for business, BI vs data science , data analytics tools, data science lifecycle along with a demo. This Data Science tutorial video is ideal for beginners to learn data science and machine learning basics. You can read the blog here: https://goo.gl/lYb5Lb Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://www.youtube.com/playlist?list=PLpF-Cn8-Vi9QC5TLuzTsl1VVuj9IwauHx #whatisdatascience #Datasciencetutorial #Datasciencecourse #datascience RR itec Services 1. There will be 150 hours of instructor-led interactive online classes with theory and practical. 2. Presentations and lab material with screenshotwise for R and python with Data science 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! About DATASCIENCE WITH PYTHON Course: 1)PYTHON BASIC LEVEL 2)PYTHON ADVANCED LEVEL 3)PYTHON PACKAGES FOR DATASCIENCE 4)MACHINE LEARNING WITH PYTHON 5)NATURAL LANGUAGE PROCESS WITH PYTHON 6)DEEP LEARNING WITH PYTHON 7)PROJECT ON NATURAL LANGUAGE PROCESS 8)PROJECT ON DEEP LEARNING About DATASCIENCE WITH R LANGUAGE Course: 1)R LANGUAGE BASIC LEVEL 2)R LANGUAGE ADVANCED LEVEL 3)R LANGUAGE PACKAGES FOR DATASCIENCE 4)MACHINE LEARNING WITH R LANGUAGE 5)NATURAL LANGUAGE PROCESS WITH R LANGUAGE 6)DEEP LEARNING WITH R LANGUAGE 7)PROJECT ON NATURAL LANGUAGE PROCESS 8)PROJECT ON DEEP LEARNING follow us on: facebook:https://www.facebook.com/rritec/ twitter:https://twitter.com/rritec linkedin:https://www.linkedin.com/in/rritec/ google plus:https://plus.google.com/1046387232991... For more Videos:https://www.youtube.com/results?searc... More details: Phone no:8374899166,8790998182 Website: www.datahexa.com Mail id :[email protected] Youtube channel link: https://www.youtube.com/user/rritec Info mail:[email protected] https://datahexa.com/account/?action=..
Views: 127 RR ITEC
Machine Learning course overview and introduction
 
24:46
In this video, we shall cover introduction to ML and the course overview. B0: PRE REQUISITES: 1 mathematics: prob ,probability distribution function(PDF),normal dist,tranformations: Fourier transform,linear algebra : linear , quad and poly,coordinate geo,diff calc. 2. programming lang: python + R 3.statistics.: 20 classes B1: PREDICTIVE MODELLING: 1.linear regression: 2.logistic regression. 3.detecing outliers. 4 classes B2.DATA SCIENCE: framework : sci kit learn/sk learn. 1.intro to DS. 2.numpy : numerical python. 3.pandas : large datset( csv,tsv,xls,json,html) 3.Dataframes.: data handling and manipulation. 4.data extraction and mining: bs4 5.analyze the given data using pandas. 6.perform operations on that data. 7. visualzation : matplotlib,seaborn. Bokeh.: used to viusalize > 3 D data. 20 CLASSES Libraries for DS: jupyter notebook. Numpy,Pandas ,matplotlib,seaborn,bokeh,scipy[ applied statistics ]. B3. Applied ML: 1.intro to ML. 2. decision trees. 3.random forest. 4.naive bayes: text clf. bayes theorem : P(a/b)=p(b/a)/p(b)*p(a): 5.KNN : k nearest neighbours. 6. K Means clustering : 7.support vector machines: 1.svc 2.svr 8.boosting and bagging. 15 CLASSES B4. Applied ML 2: 1. customizing algos acc to the problem stmt. 2. apriori alg: recommendation engine : 3.eclat Algo. 5 CLASSES Case study: B5.Deep learning and AI: 1.hype behind DL. 2.keras  framework. 3.tensorflow “ ” 4. basics of Neural networks. 5.MLP: multi layer perceptron.: Scikit learn. 6.ANN : arttificial NN. 7.CNN: convolutional NN: image processing ,video analytics and img recognition. 8.RNN : recurrent NN: for text data. 9.LSTM : long short term memory. For large text data. 10 Casestudy:1. how to build a simple seq2seq translator using DL. 2.How to build a chatbot.(speech detection and audio analytics.) 1.Wat is AI. 2.AI agent? 3.AI enviornment>? 4.reward? 5.rewrd policy. 5CLASSES Casetudy: AI agent to play any game:doom,candy crush. Casestudy : Self driving car. Framework : openAI gym.
Views: 104 6Benches
Python BeautifulSoup Modülü Kullanımı - 2
 
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Python Requests ve Python BeautifulSoup modülünü kullanarak boxofficeturkiye sitesine girdik ve son 20 filmin datasını çektik, bu modüller ile python dilinde bir bot yazabilirsiniz. Python eğitimi ve python derslerimizde mutlaka öğrenmemiz gereken python beautifulsoup modülününün kullanımını anlattım. BeautifulSoup ile ilgili Blog Yazım: http://www.sinanerdinc.com/python-beautifulsoup-modulu Requests modülü ile ilgili blog yazım: http://www.sinanerdinc.com/python-requests-modulu Requests modülü video eğitimi: https://www.youtube.com/watch?v=3yLrXiZEsBg Yazdığım Kodlar: https://github.com/sinanerdinc/ParseHtml/blob/master/boxoffice.py
Views: 1413 Sinan Erdinç
python string split by separator
 
03:22
Code and details: Code from the video: http://blog.softhints.com/python-string-split-by-separator/ Other examples: http://blog.softhints.com/python-split-string-into-list-examples/ Simple python split string Split by multiple separators Regex to extract words and digits Split string by string --------------------------------------------------------------------------------------------------------------------------------------------------------------- If you really find this channel useful and enjoy the content, you're welcome to support me and this channel with a small donation via PayPal and Bitcoin. PayPal donation https://www.paypal.me/fantasyan Bitcoin: 1DBZu6N9JTpRDdc9QChLZnX3v2iVRaQ4ym Programming is a fun! :) Site: www.softhints.com Facebook: www.facebook.com/Softhints/ Twitter: www.twitter.com/SoftwareHints
Views: 155 Softhints
How to automate google search | Google search from Linux terminal | googler install and use
 
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In this tutorial, Lets learn how to perform google search directly from command prompt. HOw to download and and install googler google search tool in LInux terminal Installation steps in Linux/AIX: cd /home/shanky git clone https://github.com/jarun/googler.git cd googler sudo make install cd auto-completion/bash/ sudo cp googler-completion.bash /etc/bash_completion.d/ Please subscribe to my youtube channel for such tutorials Please watch the split a file by line number here: https://youtu.be/ADRmbu3puCg Split utility in Linux/Unix : to break huge file into small pieces https://www.youtube.com/watch?v=ADRmbu3puCg How to keep sessions alive in terminal/putty infinitely in linux/unix : Useful tips https://www.youtube.com/watch?v=ARIgHdpxaU8 Random value generator and shuffling in python https://www.youtube.com/watch?v=AKwnQQ8TBBM Intro to class in python https://www.youtube.com/watch?v=E6kKZXHS5hM Lists, tuples, dictionary in python https://www.youtube.com/watch?v=Axea1CSewzc Python basic tutorial for beginners https://www.youtube.com/watch?v=_JyjbZc0euY Python basics tutorial for beginners part 2 -variables in python https://www.youtube.com/watch?v=ZlsptvP69NU Vi editor basic to advance part 1 https://www.youtube.com/watch?v=vqxQx-NNyFM Vi editor basic to advance part 2 https://www.youtube.com/watch?v=OWKp2DLaFyY Keyboard remapping in linux, switching keys as per your own choice https://www.youtube.com/watch?v=kJz7uKDyZjs How to install/open an on sceen keyboard in Linux/Unix system https://www.youtube.com/watch?v=d71i9SZX6ck Python IDE for windows , linux and mac OS https://www.youtube.com/watch?v=-tG54yoDs68 How to record screen or sessions in Linux/Unix https://www.youtube.com/watch?v=cx59c15-c8s How to download and install PAGE GUI builder for python https://www.youtube.com/watch?v=dim725Px2hM Create a basic Login page in python using GUI builder PAGE https://www.youtube.com/watch?v=oCAWWUhwEUQ Working with RadioButton in python in PAGE builder https://www.youtube.com/watch?v=YJbQvpzJDr4 Basic program on Multithreading in python using thread module https://www.youtube.com/watch?v=RGm3989ekAc
Views: 129 LinuxUnixAix
R Spatial Data 2: KNN from Longitude and Latitude
 
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Here I read in some longitude and latitudes, and create a K nearest neighbor weights file. Then we visualize with a plot, and export the weights matrix as a CSV file. Link to R Commands: http://spatial.burkeyacademy.com/home/files/knn%20in%20R.txt Link to Spatial Econometrics Cheat Sheet: http://spatial.burkeyacademy.com/home/files/BurkeyAcademy%20Spatial%20Regression%20CheatSheet%200.6.pdf Link to Census Site: https://www.census.gov/geo/reference/centersofpop.html Great Circle Distances: https://youtu.be/qi9KIKDpHKY My Website: spatial.burkeyacademy.com or www.burkeyacademy.com Support me on Patreon! https://www.patreon.com/burkeyacademy Talk to me on my SubReddit: https://www.reddit.com/r/BurkeyAcademy/
Views: 3259 BurkeyAcademy
Stop words
 
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In computing, stop words are words which are filtered out prior to, or after, processing of natural language data (text). There is not one definite list of stop words which all tools use and such a filter is not always used. Some tools specifically avoid removing them to support phrase search. Any group of words can be chosen as the stop words for a given purpose. For some search machines, these are some of the most common, short function words, such as the, is, at, which, and on. In this case, stop words can cause problems when searching for phrases that include them, particularly in names such as 'The Who', 'The The', or 'Take That'. Other search engines remove some of the most common words—including lexical words, such as "want"—from a query in order to improve performance. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 629 Audiopedia
Python Function| Distance formula
 
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Function to compute distance between points- In this video you will learn how to write a function to compute distance between two points in two dimensional and three dimensional planes Visit us : http://analyticuniversity.com/
Views: 10028 Analytics University
python dersleri 05 requests ve beautifulsoup
 
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Beşinci python dersimizde Requests ve BeautifulSoup paketlerini kullanıyoruz. Hazırladığımı kodlar hem python 2, hem de python 3 serisinde aynen çalışmaktadır. Videoda işlenen kaynak kodlarına: http://gurmezin.com/python-requests-ve-beautifulsoup-paketleri/ adresinden ulaşabilirsiniz.
Views: 1160 Ahmet Aksoy
NaiveBayes example
 
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Simple example of the Naive Bayes classification algorithm
Views: 137319 Francisco Iacobelli
How decision trees algorithm works
 
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In this video we describe how the decision tree algorithm works, how it selects the best features to classify the input patterns. Based on the C4.5 algorithm strategy, proposed by Quinlan, 1993.
Views: 65039 Thales Sehn Körting
How K-Means algorithm works
 
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In this video I describe how the K-Means algorithm works, and provide a simple example using 2-dimensional data and K=3.
Views: 157094 Thales Sehn Körting
파이썬 강좌 | Python MOOC |  데이터과학을 위한 파이썬 입문 Intro
 
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기존 강좌를 업데이트하여 인프런에 새롭게 강좌를 오픈하였습니다. https://www.inflearn.com/course/python-%ED%8C%8C%EC%9D%B4%EC%8D%AC-%EC%9E%85%EB%AC%B8-%EA%B0%95%EC%A2%8C/ K-MOOC: 데이터 과학을 위한 파이썬 입문 강좌 http://www.kmooc.kr/courses/course-v1:GachonUnivK+ACE.GachonUnivK01+2016_01/about 본 강의는 교육부의 "K-MOOC 강좌개발지원 사업"의 일환으로 가천대학교 ACE 사업단에 의해 제작되었습니다. 본 강의는 가천대학교 ACE 사업단의 데이터 과학 시리즈 MOOC의 일환으로 제작됩니다. 본 과정은 아래와 같이 구성됩니다. 강의 개요 강좌명: Gachon CS50 - 데이터 과학을 위한 파이썬 입문 강의자명: 가천대학교 산업경영공학과 최성철 교수 ([email protected], Director of TeamLab) Facebook: Gachon CS50 강의자료: Docs.com Email: [email protected] 강의 구성 1주차: 프로그래밍과 파이썬 2주차: 메모리와 변수 (Memory & Variable) 3주차: 화면 입출력과 리스트 다루기 (Console & List Data Type) 4주차: 제어문과 반복문 (Condition & Loop) 5주차: 함수와 파이썬 코드 작성연습 6주차: 파이썬 문자열 다루기 (String) 7주차: 파이썬 자료 구조 (Data Structure) 8주차: 파이썬같은 코드 작성하기 (Pythonic Code) 9주차: 파이썬 객체 지향 프로그래밍 (Objective-Oriented Programming) 10주차: 모듈과 패키지 (Module & Packages) 11주차: 예외 처리 (Exception Handling) 12주차: 파일 다루기와 CSV (File Handling and Comma Separate Values) 13주차: Web Scraping 14주차: XML과 JSON (eXtensible Markup Languages and JSON) 15주차: What is NEXT? 참고자료 - 점프 투 파이썬, 박응용 지음 , 2014 - 헬로 파이썬 프로그래밍, 워렌 산데,카터 산데 지음 / 김승범, 박준표 옮김 , 2014 - 파이썬 바이블3, 이강성 지음, 2013 하용호, 스타트업 데이터를 어떻게 봐라봐야 할까 , 2014 강철, [PyConKR 2014] 30분만에 따라하는 동시성 스크래퍼 , 2014 정민영, [2D4] Python에서의 동시성_병렬성, 2014 최성철, 산업공학과를 위한 프로그래밍 입문 Part 1(w/파이썬) , 2014 최성철, 산업공학과를 위한 프로그래밍 입문 Part 2(w/파이썬) , 2014 최성철, 산업공학과를 위한 프로그래밍 입문 Code(w/파이썬) , 2014
Views: 134689 TeamLab
BASH scripting lesson 10 working with CSV files
 
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More videos like this online at http://www.theurbanpenguin.com We now have some more great fun and see how much we can use the shell for; creating reports easily from the command line against CSV files. The script should be quite easy to read now as we use a while loop to read in the CSV file. We change the file delimiter to be the comma and then we have the line that we read in broken up into the schema elements we need. A report then is easy with colours and search ability. This is very usable
Views: 56452 theurbanpenguin
Tutorial: Optimization modeling with IBM ILOG CPLEX Optimization Studio
 
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This is the second in a three-part video series that introduces IBM ILOG CPLEX Optimization Studio. In this video, we look at how we can quickly get started with creating an optimization model in the Optimization Programming Language (OPL) and Python. You can explore IBM ILOG CPLEX Optimization Studio in greater detail by visiting: https://ibm.co/2JFDNTx CPLEX Fundamentals Tutorial: https://ibm.co/2Jwd14a Optimization models in Python: https://ibm.co/2JtuKsK Please note that the transcript for this video has been translated into French, German, Spanish, and Simplified Chinese. To view the subtitles, click on the 'Settings' icon on the bottom right of the video, click on 'Subtitles,' and then select what language you want to view the transcript in
Views: 10352 IBM Analytics
R tutorial: Data splitting and confusion matrices
 
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Learn more about credit risk modeling in R: https://www.datacamp.com/courses/introduction-to-credit-risk-modeling-in-r We have seen several techniques for preprocessing the data. When the data is fully preprocessed, you can go ahead and start your analysis. You can run the model on the entire data set, and use the same data set for evaluating the result, but this will most likely lead to a result that is too optimistic. One alternative is to split the data into two pieces. The first part of the data, the so-called training set, can be used for building the model and the second part of the data, the test set, can be used to test the results. One common way of doing this is to use two-thirds of the data for a training set and one-third of the data for the test set. Of course there can be a lot of variation in the performance estimate depending which two-thirds of the data you select for the training set. One way to reduce this variation is by using cross validation. For the two-thirds training set and one-third test set example, a cross validation variant would look like this. The data would be split in three equal parts, and each time, two of these parts would act as a training set, and one part would act as a test set. Of course, we could use as many parts as we want, but we would have to run the model many times if using many parts. This may become computationally heavy. In this course, we will just use one training set and one test set containing two-thirds versus one-third of the data, respectively. Imagine we have just run a model, and now we apply the model to our test set to see how good the results are. Evaluating the model for credit risk means comparing the observed outcomes of default versus non-default--stored in the loan_status variable of the test set--with the predicted outcomes according to the model. If we are dealing with a large number of predictions, a popular method for summarizing the results uses something called a confusion matrix. Here, we use just 14 values to demonstrate the concept. A confusion matrix is a contingency table of correct and incorrect classifications. Correct classifications are on the diagonal of the confusion matrix. We see, for example, that 8 non-defaulters were correctly classified as non-default, and 3 defaulters were correctly classified as defaulters. However, we see that 2 non-defaulters where wrongly classified as defaulters, and 1 defaulter was wrongly classified as a non-defaulter. The items on the diagonals are also called the true positives and true negatives. The off-diagonals are called the false positives versus the false negatives. Several measures can be derived from the confusion matrix. We will discuss the classification accuracy, the sensitivity and the specificity. The classification accuracy is the percentage of correctly classified instances, which is equal to 78.57% in this example. The sensitivity is the percentage of good customers that are classified correctly, or 75% in this example. The specificity is the percentage of bad costomers that are classified correctly, or 0.80 in this example. Let's practice splitting the data and constructing confusion matrices.
Views: 16483 DataCamp
Microsoft Build 2019 - LIVE Stream - Day 2 (May 7)
 
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To watch more sessions and ask questions live on air head over to https://aka.ms/MicrosoftBuildLive
Views: 16208 Microsoft Developer
Java prog#14.How to Insert/Save data from netbeans java into database Sqlite (MySql)
 
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------------------Online Courses to learn---------------------------- Java - https://bit.ly/2H6wqXk C++ - https://bit.ly/2q8VWl1 AngularJS - https://bit.ly/2qebsLu Python - https://bit.ly/2Eq0VSt C- https://bit.ly/2HfZ6L8 Android - https://bit.ly/2qaRSAS Linux - https://bit.ly/2IwOuqz AWS Certified Solutions Architect - https://bit.ly/2JrGoAF Modern React with Redux - https://bit.ly/2H6wDtA MySQL - https://bit.ly/2qcF63Z ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL -------------------------Stuff I use to make videos ------------------- Stuff I use to make videos Windows notebook – http://amzn.to/2zcXPyF Apple MacBook Pro – http://amzn.to/2BTJBZ7 Ubuntu notebook - https://amzn.to/2GE4giY Desktop - http://amzn.to/2zct252 Microphone – http://amzn.to/2zcYbW1 notebook mouse – http://amzn.to/2BVs4Q3 ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter netbeans java tutorial how to insert data from netbeans into database Insert information into a MySQL database - NetBeans - Java Insert Data Into Mysql Database Using Netbeans Insert Data Of Textfields In Database "netbeans"‎ Insert Data Into Database Using Netbeans to insert, update and delete new data into mysql database using jbutton. How to insert data into database how to insert java.sql.data into database sql - Java Date - Insert into database How to Insert Data into a table in mysql database insert values in table,JDBC Insert Row JDBC program to insert data into mysql database from java netbeans iit Learn java netbeans java tutorial netbeans
Views: 195119 ProgrammingKnowledge
Merkle Tree
 
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This is a spoken word version of the article Merkle Tree. Listen to this article (audio help) Duration: 04:45 Created by: slashdottir Date recorded: 2013-09-17 Corresponding article version: Click here to see the article as it was read Accent: Californian English Refer to: List of spoken articles Wikiproject Spoken Wikipedia Source: https://commons.wikimedia.org/wiki/File:En-Merkle_Tree.ogg License: CC-BY-SA 3.0 Picture: By Azaghal (Own work) [CC0], via Wikimedia Commons https://commons.wikimedia.org/wiki/File%3AHash_Tree.svg
Views: 15354 Spoken Wikipedia