Book Image

Keras 2.x Projects

By : John Bura
Book Image

Keras 2.x Projects

By: John Bura

Overview of this book

Keras is a Python library that provides a simple and clean way to create a range of deep learning models. This course introduces you to Keras and shows you how to create applications with maximum readability. You take your first steps by getting introduced to Keras, its benefits, and its applications. As you get comfortable with Keras, you will learn how to predict business outcomes using time series data and various forecasting techniques. By learning the basic concepts of reinforcement learning, you will be able to create algorithms that can learn and adapt to environmental changes and control your robots. Then, you will learn various natural language processing techniques and use the Natural Language Toolkit to analyze, classify, and tag text. By the end of the course, you’ll have the skills and the confidence to work on existing deep learning projects or create your own applications. The code bundle for this course can be downloaded from here: https://github.com/TrainingByPackt/Keras-2.X-Projects-eLearning
Table of Contents (4 chapters)
Chapter 3
Robot Control System Using Deep Reinforcement Learning
Content Locked
Section 4
Reinforcement Learning Basics
Reinforcement learning aims to create algorithms that can learn and adapt to environmental changes. This programming technique is based on the concept of receiving external stimuli that depend on the actions chosen by the agent. A correct choice will involve a reward, while an incorrect choice will lead to a penalty. The goal of the system is to achieve the best possible result, of course. Here are the topics that we will cover now: - Reinforcement Learning Basics - Agent's Interaction with the Environment - Agent-Environment Interface - Agent-Environment - Reinforcement Learning Terminology - Reinforcement Learning Algorithms - Decision Process (DP) - Policy - Monte Carlo (MC) Methods - Temporal Difference (TD) Learning