Book Image

Statistics for Machine Learning

By : Pratap Dangeti
Book Image

Statistics for Machine Learning

By: Pratap Dangeti

Overview of this book

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 book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more. By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem.
Table of Contents (16 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Temporal difference learning


Temporal Difference (TD) learning is the central and novel theme of reinforcement learning. TD learning is the combination of both Monte Carlo (MC) and Dynamic Programming (DP) ideas. Like Monte Carlo methods, TD methods can learn directly from the experiences without the model of environment. Similar to Dynamic Programming, TD methods update estimates based in part on other learned estimates, without waiting for a final outcome, unlike MC methods, in which estimates are updated after reaching the final outcome only.

Comparison between Monte Carlo methods and temporal difference learning

Though Monte-Carlo methods and Temporal Difference learning have similarities, there are inherent advantages of TD-learning over Monte Carlo methods.

Monte Carlo methods

Temporal Difference learning

MC must wait until the end of the episode before the return is known.

TD can learn online after every step and does not need to wait until the end of episode.

MC has high variance and low...