Deep Reinforcement Learning: Hands-on AI Tutorial in Python

BY
Udemy

Mode

Online

Fees

₹ 499 2299

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 499  ₹2,299
certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Introduction

  • Introduction
  • Course Structure
  • Environment Setup

Jump into Reinforcement Learning

  • Introduction
  • RL Applications
  • RL vs. Supervised and Unsupervised Learning
  • What is reinforcement learning?

RL Algorithms

  • Markov Decision Process
  • Optimal Policy
  • Bellman Equation
  • Q-Learning
  • Step-by-step Example
  • Sarsa
  • Deep Q-Network
  • Exploration vs. Exploitation
  • Define RL Problem - Examples
  • Reinforcement learning algorithms
  • SARSA algorithm

Hands-on Project 1 - Maze Problem

  • Overall Design
  • Create Project
  • Create files
  • Create Maze Environment class
  • Implement Building Maze Grid
  • Test build_maze method
  • Render and Reset methods
  • Implement getting next state and reward
  • Create Agent class
  • Implement adding states
  • Implement choosing action
  • Implement learn method
  • Create App
  • Implement main method
  • Implement plotting results
  • Run the App
  • Expand Maze Environment

Hands-on Project 2 - Stock Trading

  • Overall Design
  • Start project
  • Prepare dataset
  • Create Market Environment class
  • Implement getting data
  • Implement getting all states
  • Implement getting next state and reward
  • Create Agent class
  • Implement creating deep learning model and reset method
  • Implement getting action
  • Implement buy and sell
  • Implement experience replay
  • Create training app
  • Test training app
  • Create evaluation app
  • Implement plotting results
  • Run training and evaluation
  • Extending Stock Trading with Multiple Features
  • Multiple Feature Stock Trader

Summary

  • Summary

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