** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 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 have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 52710 edureka!
Gource visualization of pattern (https://github.com/clips/pattern) [03-08-2019]. Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization. This visualization was generated with the following command: gource --path path/to/repo --seconds-per-day 0.15 --title "pattern" -1280x720 --file-idle-time 0 --auto-skip-seconds 0.75 --multi-sampling --stop-at-end --key --highlight-users --hide filenames,mouse,progress,bloom --max-files 0 --background-colour 000000 --font-size 24 --output-ppm-stream - --output-framerate 30 -o - | ffmpeg -y -r 60 -f image2pipe -vcodec ppm -i - -i path/to/music.mp3 -shortest -vcodec libx264 -preset ultrafast -pix_fmt yuv420p -crf 1 -threads 0 -bf 0 path/to/output.mp4 Installation (OS X): brew install gource brew install ffmpeg More information: http://gource.io/ https://github.com/acaudwell/Gource Why make this visualization? - I'm studying how popular projects evolve Music: Song: Deep Hat Artist: Vibe Tracks Source: YouTube Audio Library (Free Music) ---
Views: 4 Landon Wilkins
Learn Python here: https://courses.learncodeonline.in/learn/Python3-course In this video, we will talk about basics of web scraping using python. This is a video for total beginners, please comment if you want more videos on web scraping fb: https://www.facebook.com/HiteshChoudharyPage homepage: http://www.hiteshChoudhary.com Download LearnCodeOnline.in app from Google play store and Apple App store
Views: 192467 Hitesh Choudhary
In this video we'll be creating a really simple web server in Python using the Python http library. Go to https://howcode.org for more! Source code: https://howco.de/simple-python-web-server Link to DigitalOcean: http://howco.de/d_ocean Link to howCode Facebook: http://howco.de/fb Link to howCode Twitter: http://howco.de/twitter Link to /r/howCode: http://howco.de/reddit Don't forget to subscribe for more!
Views: 54920 howCode
In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 590101 Siraj Raval
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: 335649 sentdex
This is part 2 of an introductory web scraping tutorial. In this video, we'll read a New York Times article into Python, and then use the Beautiful Soup library to parse the HTML based on patterns in the article's formatting. Watch the 4-video series: https://www.youtube.com/playlist?list=PL5-da3qGB5IDbOi0g5WFh1YPDNzXw4LNL == RESOURCES == Download the Jupyter notebook: https://github.com/justmarkham/trump-lies New York Times article: https://www.nytimes.com/interactive/2017/06/23/opinion/trumps-lies.html requests documentation: http://docs.python-requests.org/en/master/ Beautiful Soup documentation: https://www.crummy.com/software/BeautifulSoup/bs4/doc/ == DATA SCHOOL VIDEOS == Machine learning with scikit-learn: https://www.youtube.com/watch?v=elojMnjn4kk&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=1 Data analysis with pandas: https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=1 Version control with Git: https://www.youtube.com/watch?v=xKVlZ3wFVKA&list=PL5-da3qGB5IBLMp7LtN8Nc3Efd4hJq0kD&index=1 == SUBSCRIBE FOR MORE VIDEOS == https://www.youtube.com/user/dataschool?sub_confirmation=1 == JOIN THE DATA SCHOOL COMMUNITY == Newsletter: http://www.dataschool.io/subscribe/ Twitter: https://twitter.com/justmarkham Facebook: https://www.facebook.com/DataScienceSchool/ Patreon: https://www.patreon.com/dataschool
Views: 44928 Data School
This video demonstrates the concept of fuzzy string matching using fuzzywuzzy in Python. Explore my tutorials: https://www.indianpythonista.tech/tutorials/ More awesome topics covered here: WhatsApp Bot using Twilio and Python: http://bit.ly/2JmZaNG Discovering Hidden APIs: http://bit.ly/2umeMHb RegEx in Python: http://bit.ly/2Hhtd6L Introduction to Numpy: http://bit.ly/2RZMxvO Introduction to Matplotlib: http://bit.ly/2UzwfqH Introduction to Pandas: http://bit.ly/2GkDvma Intermediate Python: http://bit.ly/2sdlEFs Functional Programming in Python: http://bit.ly/2FaEFB7 Python Package Publishing: http://bit.ly/2SCLkaj Multithreading in Python: http://bit.ly/2RzB1GD Multiprocessing in Python: http://bit.ly/2Fc9Xrp Parallel Programming in Python: http://bit.ly/2C4U81k Concurrent Programming in Python: http://bit.ly/2BYiREw Dataclasses in Python: http://bit.ly/2SDYQub Exploring YouTube Data API: http://bit.ly/2AvToSW Jupyter Notebook (Tips, Tricks and Hacks): http://bit.ly/2At7x3h Decorators in Python: http://bit.ly/2sdloX0 Inside Python: http://bit.ly/2Qr9gLG Exploring datetime: http://bit.ly/2VyGZGN Computer Vision for noobs: http://bit.ly/2RadooB Python for web: http://bit.ly/2SEZFmo Awesome Linux Terminal: http://bit.ly/2VwdTYH Tips, tricks, hacks and APIs: http://bit.ly/2Rajllx Optical Character Recognition: http://bit.ly/2LZ8IfL Facebook Messenger Bot Tutorial: http://bit.ly/2BYjON6 Facebook: https://www.facebook.com/IndianPythonista/ Github: https://www.github.com/nikhilkumarsingh/ Twitter: https://twitter.com/nikhilksingh97 #python #fuzzy #string-matching
Views: 14149 Indian Pythonista
There is an abundance of data in social media sites (Wikipedia, Facebook, Instagram, etc.) which can be accessed through web APIs. But how do we know that the data from the Wikipedia article on "Golden Gate Bridge" goes along with the data from "Golden Gate Bridge" Facebook page? This represents an important question about integrating data from various sources. In this talk, I'll outline important aspects of structured data mining, integration and entity resolution methods in a scalable system.
Views: 5589 PyTexas
Telegram (for Live events, Quick Questions): http://t.me/letsautomate This tutorial focuses on very basic yet powerful operations in Python, to extract meaningful information from junk data. The overall video is covers these 4 points. 1. Basic string operations for data extraction 2. How to open a text file 3. How to read rows line by line 4. Data extraction from junk Feel free to write to me with suggestions and feedback. Stay connected!
Views: 8536 Extreme Automation - Kamal Girdher
In this tutorial we will make a web crawler/web scraper in Python using Selenium that will fetch the 3 days weather forecast. Link to download Chrome webdriver https://sites.google.com/a/chromium.org/chromedriver/downloads Link to download Chrome webdriver https://github.com/mozilla/geckodriver/releases Link to my blog http://www.letscodepro.com/ Complete Source Code on GitHub https://github.com/the-javapocalypse/weather-forecaster-using-selenium Please Subscribe! And like. And comment. That's what keeps me going. Follow Me Facebook: https://www.facebook.com/javapocalypse Instagram: https://www.instagram.com/javapocalypse
Views: 7683 Javapocalypse
Finally, the moment we've all been waiting for and building up to. A live test! We've decided to employ this classifier to the live Twitter stream, using Twitter's API. We've already covered how to do live Twitter API streaming, if you missed it, you can catch up here: http://pythonprogramming.net/twitter-api-streaming-tweets-python-tutorial/ After this, we output the findings to a text file, which we intend to graph! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 85731 sentdex
Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool. Code for this video: https://github.com/llSourcell/Predicting_Winning_Teams Please Subscribe! And like. And comment. More learning resources: https://arxiv.org/pdf/1511.05837.pdf https://doctorspin.me/digital-strategy/machine-learning/ https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/ http://data-informed.com/predict-winners-big-games-machine-learning/ https://github.com/ihaque/fantasy https://www.credera.com/blog/business-intelligence/using-machine-learning-predict-nfl-games/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 103004 Siraj Raval
** Python Certification Training: https://www.edureka.co/python ** This Edureka video on Python Projects will help you establish a foothold on Python by helping you assess and obtain skills which are used to design, develop and analyze projects built in Python. 1. Introduction to Python 2. Installation and Working with Python 3. Python Projects- 3levels 4. Practical approach - Code Python Tutorial Playlist: https://goo.gl/WsBpKe Blog Series: http://bit.ly/2sqmP4s #pythonprojects #pythonprogramming #pythontutorial #PythonTraining #PythonEdureka #Edureka Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV 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 ----------------------------------------------------------------------------------------------------------------------------------- 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 Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in Python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in Python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enable the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 74389 edureka!
Intersys’ Data Scientist Jaya Zenchenko for a visual demonstration of topic modeling using python showing how data science can turn big quantities of data into something actionable. In this visual example, you will see how large amounts of text can be turned into automatically categorized and summarized inventory. In this fun approach of “what to wear” and maybe “what not to wear”, Jaya will cover topics such as web scraping, text mining and document clustering all within the python data science stack using tools such as Jupyter, Notebooks, Beautiful Soup, pandas and scikit-learn.
Views: 3549 Intersys Consulting
The analysis of time series data is a fundamental part of many scientific disciplines, but there are few resources meant to help domain scientists to easily explore time course datasets: traditional statistical models of time series are often too rigid to explain complex time domain behavior, while popular machine learning packages deal almost exclusively with 'fixed-width' datasets containing a uniform number of features. Cesium is a time series analysis framework, consisting of a Python library as well as a web front-end interface, that allows researchers to apply modern machine learning techniques to time series data in a way that is simple, easily reproducible, and extensible.
Views: 43560 Enthought
✅ Algorithms and Data Structures Masterclass: http://bit.ly/algorithms-masterclass-java ✅ FREE Java Programming Course: http://bit.ly/first-steps-java ✅ FREE Top Programming Interview Questions: http://bit.ly/top-programming-intervi... ✅ Full Numerical Methods Course: http://bit.ly/numerical-methods-java ✅ Find more: https://www.globalsoftwaresupport.com/ ===================================================== In this course we are going to consider the most relevant numerical methods that are being used on a daily basis. We'll implement the algorithms in Java ✘ matrix operations ✘ how to calculate the inverse of a matrix (Gauss-elimination) ✘ numerical integration ✘ solving differential equations ✘ Euler's method and Runge-Kutta method ===================================================== ✅ Instagram: https://www.instagram.com/global.software.algorithms/ ✅ Facebook: https://www.facebook.com/Global-Software-Support-2420513901306285/
Views: 82894 Balazs Holczer
No need to scrape google to fetch web and image search results! Learn how to work with Google Custom Search Engine using Python in this video. Reference Material here: https://gist.github.com/nikhilkumarsingh/5bce182ed57ae73f6cbde52fe846991b Explore my tutorials: https://www.indianpythonista.tech/tutorials/ More awesome topics covered here: WhatsApp Bot using Twilio and Python: http://bit.ly/2JmZaNG Discovering Hidden APIs: http://bit.ly/2umeMHb RegEx in Python: http://bit.ly/2Hhtd6L Introduction to Numpy: http://bit.ly/2RZMxvO Introduction to Matplotlib: http://bit.ly/2UzwfqH Introduction to Pandas: http://bit.ly/2GkDvma Intermediate Python: http://bit.ly/2sdlEFs Functional Programming in Python: http://bit.ly/2FaEFB7 Python Package Publishing: http://bit.ly/2SCLkaj Multithreading in Python: http://bit.ly/2RzB1GD Multiprocessing in Python: http://bit.ly/2Fc9Xrp Parallel Programming in Python: http://bit.ly/2C4U81k Concurrent Programming in Python: http://bit.ly/2BYiREw Dataclasses in Python: http://bit.ly/2SDYQub Exploring YouTube Data API: http://bit.ly/2AvToSW Jupyter Notebook (Tips, Tricks and Hacks): http://bit.ly/2At7x3h Decorators in Python: http://bit.ly/2sdloX0 Inside Python: http://bit.ly/2Qr9gLG Exploring datetime: http://bit.ly/2VyGZGN Computer Vision for noobs: http://bit.ly/2RadooB Python for web: http://bit.ly/2SEZFmo Awesome Linux Terminal: http://bit.ly/2VwdTYH Tips, tricks, hacks and APIs: http://bit.ly/2Rajllx Optical Character Recognition: http://bit.ly/2LZ8IfL Facebook Messenger Bot Tutorial: http://bit.ly/2BYjON6 Facebook: https://www.facebook.com/IndianPythonista/ Github: https://www.github.com/nikhilkumarsingh/ Twitter: https://twitter.com/nikhilksingh97 #google #custom #search #python
Views: 383 Indian Pythonista
** NIT Warangal Post Graduate Program on AI and Machine Learning: https://www.edureka.co/nitw-ai-ml-pgp ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial: 1. AI vs Machine Learning vs Deep Learning 2. What is Artificial Intelligence? 3. Example of Artificial Intelligence 4. What is Machine Learning? 5. Example of Machine Learning 6. What is Deep Learning? 7. Example of Deep Learning 8. Machine Learning vs Deep Learning Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV 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 Telegram: https://t.me/edurekaupdates - - - - - - - - - - - - - - - - - #edureka #AIvsMLvsDL #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). 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: 521310 edureka!
Views: 895 Joe James
This Data Science with Python Tutorial will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python. The aim of this video is to provide a comprehensive knowledge to beginners who are new to Python for data analysis. This video provides a comprehensive overview of basic concepts that you need to learn to use Python for data analysis. Now, let us understand how Python is used in Data Science for data analysis. This Data Science with Python tutorial will cover the following topics: 1. What is Data Science? 2. Basics of Python for data analysis - Why learn Python? - How to install Python? 3. Python libraries for data analysis 4. Exploratory analysis using Pandas - Introduction to series and dataframe - Loan prediction problem 5. Data wrangling using Pandas 6. Building a predictive model using Scikit-learn - Logistic regression 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/ifQRpS 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 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=Data-Science-With-Python-mkv5mxYu0Wk&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn 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: 96320 Simplilearn
Deep Learning Crash Course playlist: https://www.youtube.com/playlist?list=PLWKotBjTDoLj3rXBL-nEIPRN9V3a9Cx07 Highlights: Garbage-in, Garbage-out Dataset Bias Data Collection Web Mining Subjective Studies Data Imputation Feature Scaling Data Imbalance #deeplearning #machinelearning
Views: 2019 Leo Isikdogan
We will discuss another interesting aspect of analyzing data from Twitter - the distribution of tweets over time. Generally speaking, a time series is a sequence of data points that consists of successive observations over a given interval of time. ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 1127 Sukhvinder Singh
► SUBSCRIBE TO THIS CHANNEL ◄ Subscribe to become a highly paid blockchain developer: https://www.youtube.com/channel/UCY0xL8V6NzzFcwzHCgB8orQ?sub_confirmation=1 JOIN MY BLOCKCHAIN DEVELOPER BOOTCAMP: http://www.dappuniversity.com/bootcamp DOWNLOAD FREE VIDEO COURSES: http://www.dappuniversity.com/free-download Build Your first blockchain app: http://www.dappuniversity.com/articles/blockchain-app-tutorial Website: http://dappuniversity.com/ Donate Ether to the channel: 0x39C7BC5496f4eaaa1fF75d88E079C22f0519E7b9 Follow me on Twitter (@DappUniversity): https://twitter.com/DappUniversity Email me: [email protected]
Views: 1055 Dapp University
ArcGIS API for Python lets ArcGIS users, developers, and anyone with an ArcGIS Online subscription or ArcGIS Enterprise, leverage the Python ecosystem to automate their workflows and perform repetitive tasks by writing Python scripts. In this session, you will learn how the ArcGIS Python API can help in scripting and automating your Web GIS. It will start with an introduction of the API, who it’s for and what it can do. The session will walk through the process of getting the API through Conda and writing scripts using Jupyter Notebook. A brief tour of the API will be followed by a show and tell of some of the powerful capabilities of the API.
Views: 3037 Esri Events
In this hands-on webcast presented by Harry Percival author of Test-Driven Development with Python, you will learn: How to use TDD to build a web application from the ground up Full functional testing using the Selenium browser automation tool Unit tests for all aspects of Django: urls views models templates Who should attend this event: This live webcast is suitable for relative beginners, you should know basic Python, but if you've never used TDD or Django you should be fine. About Harry Percival After an idyllic childhood spent playing with BASIC on French 8-bit computers like the Thomson T-07 whose keys go "boop" when you press them, Harry spent a few years being deeply unhappy with Economics and management consultancy. Soon he rediscovered his true geek nature, and was lucky enough to fall in with a bunch of XP fanatics, working on the pioneering but sadly defunct Resolver One spreadsheet. He now works at PythonAnywhere LLP, and spreads the gospel of TDD world-wide at talks, workshops and conferences, with all the passion and enthusiasm of a recent convert.
Views: 12884 O'Reilly
Capturing Data, Modeling Patterns, Predicting Behavior. Capturing Data, Modeling Patterns, Predicting Behavior - Based on collecting more than 20 million blog posts and news media articles per day, Professor Jure Leskovec discusses how to mine such data to capture and model temporal patterns in the news over a daily time-scale --in particular, the succession of story lines that evolve and compete for attention. He discusses models to quantify the influence of individual media sites on the popularity of news stories and algorithms for inferring hidden networks of information flow. Learn more: http://scpd.stanford.edu/
Views: 20487 stanfordonline
We show how to build a machine learning document classification system from scratch in less than 30 minutes using R. We use a text mining approach to identify the speaker of unmarked presidential campaign speeches. Applications in brand management, auditing, fraud detection, electronic medical records, and more.
Views: 167401 Timothy DAuria
Python Core ------------ Video in English https://goo.gl/df7GXL Video in Tamil https://goo.gl/LT4zEw Python Web application ---------------------- Videos in Tamil https://goo.gl/rRjs59 Videos in English https://goo.gl/spkvfv Python NLP ----------- Videos in Tamil https://goo.gl/LL4ija Videos in English https://goo.gl/TsMVfT Artificial intelligence and ML ------------------------------ Videos in Tamil https://goo.gl/VNcxUW Videos in English https://goo.gl/EiUB4P ChatBot -------- Videos in Tamil https://goo.gl/JU2WPk Videos in English https://goo.gl/KUZ7PY Email : [email protected] LinkedIn : https://www.linkedin.com/in/sbgowtham/ YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 779 atoz knowledge
In this video Apriori algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining in hindi, Finding frequent item sets, data mining, data mining algorithms in hindi, data mining lecture, data mining tools, data mining tutorial,
Views: 266603 Well Academy
code_swarm visualization for pattern (https://github.com/clips/pattern). Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization. This visualization was generated by following this tutorial: http://derwiki.tumblr.com/post/43181171352/creating-a-codeswarm-for-your-git-repository More information: http://vis.cs.ucdavis.edu/~ogawa/codeswarm/ https://github.com/rictic/code_swarm Why make this visualization? - I'm studying how popular projects evolve Music: Song: Deep Hat Artist: Vibe Tracks Source: YouTube Audio Library (Free Music)
Views: 10 Landon Wilkins
When writing scrapers, it's important to think about the overall pattern for your code in order to handle exceptions and make it readable at the same time. You'll also likely want to reuse code. Make you scrapers scrape the web quickly and reliably. ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE "Web Scraping with Python" on Amazon: http://amzn.to/2sOGBZU ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 4858 Sukhvinder Singh
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining
Views: 52 Freemium Courses
Link to our course : http://rshankar.com/courses/autolayoutyt7/ In this course, we have been looking at Regular expressions, a tool that helps us mine text but in this video i wish to give you a flavor of a Python package called nltk. Since this course is about finding patterns in text, it is only fair that you know about another package that offers a lot of help in this direction. Reference: https://www.nltk.org/ https://en.wikipedia.org/wiki/Text_mining https://www.deviantart.com/sirenscall/art/The-Highwayman-26312892 https://www.deviantart.com/enricogalli/art/Moby-Dick-303519647 Images courtesy: Designed by Freepik from www.flaticon.com Script: If you look at jobs advertised for data analysts or data scientists, you will often come across the term - text mining It is the process of deriving useful information from text. Text mining is in itself a fascinating subject and involves tasks such as text classification, text clustering, sentiment analysis and much more. The goal of text mining is to turn text into data for analysis. In this course, we have been looking at Regular expressions, a tool that helps us mine text but in this video i wish to give you a flavor of a Python package called nltk. Since this course is about finding patterns in text, it is only fair that you know about another package that offers a lot of help in this direction. nltk stands for the natural language toolkit and is an open source community driven project. nltk helps us build Python programs to work with human language data. So for example if you wish to create a spam detection program, or movie review program, nltk offers a lot of helper functions. The goal of this video to inform you that such a package exists and show you some basic functionality. If you like what you see, do let me know and I will add more videos on this subject. So we will start with a new Jupyter notebook. I already have the nltk package . If you do not, you will need to get it, please. nltk comes with some example books. We can import these books or corpora as follows. Perhaps some of these titles may be familiar to you. So lets take Moby Dick. Its data is stored in a Text object. Can we find how many words the book contains? Ok, now how about unique words? Hmm. Less than 10 percent of the total words. An interesting thing we may wish to do is examine the frequency of words. This is often done with speeches of various politicians. So for example you may wish to see the most frequent words spoken by a politician before an election and the frequency after elections. So lets import FreqDist and assign to it the text of Moby Dick. So the keys of this object are all the words and we can see the values which are the frequency of the words. Moby Dick is a story of a whale. Lets see how many times this word figures in the book. The keys are case sensitive of course. Let us now focus on popular words in the book. But not words such as ‘has’ or ‘the’ So lets say we want to find the words of length greater than 6 which appear more than 100 times in the book. And lets sort these words for good measure. Interesting set of words. Some such as Captain would be expected i guess. Lets come back to a topic we have seen before - Word tokenization. So we have our sentence like so. And we want to break this sentence into various tokens or words. Earlier we used the function split() so lets do that again. As you can see, the output in this case bundles the full stop with a word. Also what about the word shouldn’t. Is it one token or 2? nltk provides a function that is more language syntax aware. Lets use it. I will leave you to evaluate the differences. One last thing. Here we have a slice of a wonderful poem called the HighwayMan. Now we wish to break this text into its sentences. Can we do it? Regular expressions can help but why use Regex when we have a solution. nltk offers a sent_tokenize function. Lets use it. Isn’t this poem beautiful.. Ok guys thats it for now. If you want more videos on this subject do let me know. Take care.
Views: 26 talkData
Ben Goertzel: https://en.wikipedia.org/wiki/Ben_Goertzel Hong Cogathon was held at Robotics Garage Dec 2016 http://wiki.opencog.org/w/Hong_Cogathon_Dec_2016 Many thanks for watching! Consider supporting me by: a) Subscribing to my YouTube channel: http://youtube.com/subscription_center?add_user=TheRationalFuture b) Donating via Patreon: https://www.patreon.com/scifuture and/or c) Sharing the media I create Kind regards, Adam Ford - Science, Technology & the Future: http://scifuture.org
Views: 806 Science, Technology & the Future
Simple Explanation and implementation of PNN in pyhton Inspired by Information Security Researcher, Sarah Asiri. http://sarahasiri.org/ Github: https://github.com/JaeDukSeo/probabilistic-neural-network-in-python Web site: http://jaedukseo.com/
Views: 1863 Jae duk Seo
#kmean datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 451130 Last moment tuitions
A tweet is a complex object. We will look at the attributes and their meaning. We will also look at the JSON representation of a tweet. ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 1193 Sukhvinder Singh