0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

AI Crash Course

You're reading from AI Crash Course A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python

Product type Paperback

Published in Nov 2019

Publisher Packt

ISBN-13 9781838645359

Length 360 pages

Edition 1st Edition

Languages

Python

Concepts

Artificial Intelligence

Author (1):

Hadelin de Ponteves

View More author details

Table of Contents (17) Chapters

Preface

1. Welcome to the Robot World FREE CHAPTER

2. Discover Your AI Toolkit

3. Python Fundamentals – Learn How to Code in Python

4. AI Foundation Techniques

5. Your First AI Model – Beware the Bandits!

6. AI for Sales and Advertising – Sell like the Wolf of AI Street

7. Welcome to Q-Learning

8. AI for Logistics – Robots in a Warehouse

9. Going Pro with Artificial Brains – Deep Q-Learning

10. AI for Autonomous Vehicles – Build a Self-Driving Car

11. AI for Business – Minimize Costs with Deep Q-Learning

12. Deep Convolutional Q-Learning

13. AI for Games – Become the Master at Snake

14. Recap and Conclusion

15. Other Books You May Enjoy

Leave a review - let other readers know what you think

16. Index

Summary

In this chapter you re-applied deep Q-learning to a new business problem. You were supposed to find the best strategy to cool down and heat up the server. Before you started defining the AI strategy, you had to make some assumptions about your environment, for example the way the temperature is calculated. As inputs to your ANN, you had information about the server at any given time, like the temperature and data transmission. As outputs, your AI predicted whether to cool down or heat up our server by a certain amount. The reward was the energy saved with respect to the other, traditional cooling system. Your AI was able to save 87% energy.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at ₹800/month. Cancel anytime

Authors (1)

Hadelin de Ponteves

Hadelin de Ponteves

Hadelin de Ponteves is the co-founder and CEO at BlueLife AI, which leverages the power of cutting-edge Artificial Intelligence to empower businesses to make massive profits by optimizing processes, maximizing efficiency, and increasing profitability. Hadelin is also an online entrepreneur who has created 50+ top-rated educational e-courses on topics such as machine learning, deep learning, artificial intelligence, and blockchain, which have reached over 700,000 subscribers in 204 countries.

See other products by Hadelin de Ponteves

Other recommended products

Related to this chapter

PyTorch 1.x Reinforcement Learning Cookbook

PyTorch 1.x Reinforcement Learning Cookbook

This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Oct 2019 11h 20m

PyTorch 1.x Reinforcement Learning Cookbook

PyTorch 1.x Reinforcement Learning Cookbook

This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Oct 2019 11h 20m

PyTorch 1.x Reinforcement Learning Cookbook

PyTorch 1.x Reinforcement Learning Cookbook

This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Oct 2019 11h 20m

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python

Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python

Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python

Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25h 20m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m