*** Proof of Product ***
Exploring the Essential Features of “Dr. Thomas Starke – Deep Reinforcement Learning in Trading“
What You Will Get in 25 Sessions:
- Introduction
- Need for Reinforcement Learning
- State, Actions, and Rewards
- Q Learning
- State Construction
- Policies in Reinforcement Learning
- Challenges in Reinforcement Learning
- Initialize Game Class
- Positions and Rewards
- Input Features
- Construct and Assemble State
- Game Class
- Experience Replay
- Artificial Neural Network Concepts
- Artificial Neural Network Implementation
- Backtesting Logic
- Backtesting Implementation
- Performance Analysis: Synthetic Data
- Performance Analysis: Real World Price Data
- Automated Trading Strategy
- Paper and Live Trading
- Capstone Project
- Future Enhancements
- Python Installation
- Course Summary
Please see the full list of alternative group-buy courses available here: https://lunacourse.com/shop/
