Reinforcement Learning for Finance: Solve Problems in Finance with CNN and RNN Using the TensorFlow Library - Softcover

Inhaltsangabe

Chapter 1 Overview 1.1 Methods for Training Neural Networks
Chapter 2 Convolutional Neural Networks 2.1 A Simple CNN 2.2 Identifying Technical Patterns in Security Prices
Chapter 3 Recurrent Neural Networks 3.1 LSTM Network 3.2 LSTM Application: Correlation in Asset Returns
Chapter 4 Reinforcement Learning 4.1 Basics 4.2 Methods For Estimating MDP 4.3 Value Estimation Methods 4.4 Policy Learning 4.5 Actor-Critic Algorithms 4.6; Implementation of algorithms to quantitative finance using TensorFlow - 1
Chapter 5 Recent Advances in Reinforcement Learning Algorithms 5.1 Double Deep Q-Network: DDQN 5.2 Dueling Double Deep Q-Network 5.3 Noisy Networks 5.4 Deterministic Policy Gradient

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