Advanced Statistics for Machine Learning [Video]

More Information
Learn
  • Understand artificial neural network concepts 
  • Introduce different types of Unsupervised Learning
  • Execute various models of Reinforcement Learning
About

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement.

This video will teach you all it takes to perform the complex statistical computations required for Machine Learning. You will gain information on statistics behind unsupervised learning, reinforcement learning, and more. You'll master real-world examples that discuss the statistical side of Machine Learning.

In this video, you will acquire a deep knowledge of the various models of unsupervised and reinforcement learning, and explore the fundamentals of deep learning with the help of the Keras software. Furthermore, you'll gain an overview of reinforcement learning with the Python programming language.

Style and Approach

This course applies the problem/solution approach. Each video focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.

Features
  • Implement statistical computations programmatically for unsupervised learning through K-means clustering
  • Apply the ANN classifier on handwritten digits
  • Model Blackjack example of Monte Carlo methods using Python
  • Execute the Cliff walking example of on-policy and off-policy of Temporal Difference control 
Course Length 2 hours 10 minutes
ISBN 9781788994989
Date Of Publication 27 Dec 2017

Authors

Pratap Dangeti

Pratap Dangeti is currently working as a Senior Data Scientist at Bidgely Technologies Bangalore. He has a vast experience in analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. Pratap is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.