更新时间：2021-08-13 15:26:40
封面
Title Page
Copyright and Credits
Keras Reinforcement Learning Projects
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Preface
Who this book is for
What this book covers
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Overview of Keras Reinforcement Learning
Basic concepts of machine learning
Discovering the different types of machine learning
Supervised learning
Unsupervised learning
Reinforcement learning
Building machine learning models step by step
Getting started with reinforcement learning
Agent-environment interface
Markov Decision Process
Discounted cumulative reward
Exploration versus exploitation
Reinforcement learning algorithms
Dynamic Programming
Monte Carlo methods
Temporal difference learning
SARSA
Q-learning
Deep Q-learning
Summary
Simulating Random Walks
Random walks
One-dimensional random walk
Simulating 1D random walk
Markov chains
Stochastic process
Probability calculation
Markov chain definition
Transition matrix
Transition diagram
Weather forecasting with Markov chains
Generating pseudorandom text with Markov chains
Optimal Portfolio Selection
Divide and conquer versus Dynamic Programming
Memoization
Dynamic Programming in reinforcement-learning applications
Optimizing a financial portfolio
Optimization techniques
Solving the knapsack problem using Dynamic Programming
Different approaches to the problem
Brute force
Greedy algorithms
Forecasting Stock Market Prices
Historical background
Basic concepts of the Monte Carlo simulation
Monte Carlo applications
Numerical integration using the Monte Carlo method
Monte Carlo for prediction and control
Amazon stock price prediction using Python
Exploratory analysis
The Geometric Brownian motion model
Monte Carlo simulation
Delivery Vehicle Routing Application
Basics of graph theory
The adjacency matrix
Adjacency lists
Graphs as data structures in Python
Graphs using the NetworkX package
Finding the shortest path
The Dijkstra algorithm
The Dijkstra algorithm using the NetworkX package
The Google Maps algorithm
The Vehicle Routing Problem
Continuous Balancing of a Rotating Mechanical System
Neural network basic concepts
The Keras neural network model
Classifying breast cancer using the neural network
Deep reinforcement learning
The Keras–RL package
Continuous control with deep reinforcement learning
