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Course Benefits

  • Enhance your fundamental knowledge of Machine Learning and making the use of the algorithms to the visceral level
  • Gain familiarity with database platform
  • Lean how to interface with Database from Python
  • learn about the method of classification of news article using K – Nearest Neighbors
  • Ethics of NLP and Python help in interface enhancement
  • You can maximize your employability with this training

Why to Opt for Machine Learning using Python Training?

Machine Learning is the new obsession of the technical world, the technology gives the best output when summed-up with Python. Training in Machine Learning using Python not only enhances the coding and algorithmic intelligence, but introduce you with great job opportunities around the globe. However, it is well known that programmer’s job is always been appreciated and well paid; it   is valued more when the intelligence is blended with Machine Learning and the knowledge of using Python efficiently. 
Delve into learning the popular and vastly used programming language Python in this comprehensive course comprising of 54 lectures and over 10.5 hours of content. You’ll learn how to write Python codes, how to manipulate data and automate manual work, how to scrape websites using Beautiful Soup, and a lot more. Gain expertise on machine learning techniques like sk-learn and identify how to utilize tools for text processing. The entire course is based on a hands-on approach enabling you to strengthen your knowledge and understanding by making you involved in drills and practical exercises. Be a perfectionist with this training 

Who should join
Machine Learning Using python?

  • Programming Specialists
  • Individuals having familiarity with python and willing to take the level of their skills up
  • Participants from mathematical or engineering background


  • Should have sound knowledge of Python
  • Should have programming experience

Course Contents

What is coding? – It’s a lot like cooking!
  • Introduction 
  • Coding is like Cooking 
  • Variables are like containers 
  • Anaconda and Pip 
Don’t Jump Through Hoops, Use Dictionaries, Lists and Loops
  • A List is a list 
  • Fun with Lists! 
  • Dictionaries and If-Else 
  • Don’t Jump Through Hoops, Use Loops 
  • Doing stuff with loops 
  • Everything in life is a list – Strings as lists 
Our First Serious Program
  • Modules are cool for code-reuse 
  • Our first serious program: Downloading a webpage 
  • A few details – Conditionals 
  • A few details – Exception Handling in Python 
Doing Stuff with Files
  • A File is like a barrel 
  • Autogenerating Spreadsheets with Python 
  • Autogenerating Spreadsheets – Download and Unzip 
  • Autogenerating Spreadsheets – Parsing CSV files 
  • Autogenerating Spreadsheets with XLSXwriter 
Functions are like Foodprocessors
  • Functions are like Foodprocessors 
  • Argument Passing in Functions 
  • Writing your first function 
  • Recursion 
  • Recursion in Action 
Databases – Data in rows and columns
  • How would you implement a Bank ATM? 
  • Things you can do with Databases – I 
  • Things you can do with Databases – II 
  • Interfacing with Databases from Python 
  • SQLite works right out of the box 
  • Build a database of Stock Movements – I 
  • Build a database of Stock Movements – II 
  • Build a database of Stock Movements – III 
An Object Oriented State of Mind
  • Objects are like puppies! 
  • A class is a type of variable 
  • An Interface drives behavior 
Natural Language Processing and Python
  • Natural Language Processing with NLTK 
  • Natural Language Processing with NLTK – See it in action 
  • Web Scraping with BeautifulSoup 
  • A serious NLP Application: Text Auto Summarization using Python 
  • Autosummarize News Articles – I 
  • Autosummarize News Articles – II 
  • Autosummarize News Articles – III 
Machine Learning and Python
  • Machine Learning – Jump on the Bandwagon  
  • Plunging In – Machine Learning Approaches to Spam Detection 
  • Spam Detection with Machine Learning Continued 
  • News Article Classification using K-Nearest Neighbors 
  • News Article Classification using Naive Bayes 
  • Code Along – Scraping News Websites 
  • Code Along – Feature Extraction from News articles 
  • Code Along – Classification with K-Nearest Neighbours 
  • Code Along – Classification with Naive Bayes 
  • Document Distance using TF-IDF 
  • News Article Clustering with K-Means and TF-IDF 
  • Code Along – Clustering with K-Means 

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Machine Learning Using python
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