You're reading from Artificial Intelligence By Example Acquire advanced AI, machine learning, and deep learning design skills

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781839211539

Length 578 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

Denis Rothman

View More author details

Table of Contents (23) Chapters

Preface

1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning

2. Building a Reward Matrix – Designing Your Datasets FREE CHAPTER

3. Machine Intelligence – Evaluation Functions and Numerical Convergence

4. Optimizing Your Solutions with K-Means Clustering

5. How to Use Decision Trees to Enhance K-Means Clustering

6. Innovating AI with Google Translate

7. Optimizing Blockchains with Naive Bayes

8. Solving the XOR Problem with a Feedforward Neural Network

9. Abstract Image Classification with Convolutional Neural Networks (CNNs)

10. Conceptual Representation Learning

11. Combining Reinforcement Learning and Deep Learning

12. AI and the Internet of Things (IoT)

13. Visualizing Networks with TensorFlow 2.x and TensorBoard

14. Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)

15. Setting Up a Cognitive NLP UI/CUI Chatbot

16. Improving the Emotional Intelligence Deficiencies of Chatbots

17. Genetic Algorithms in Hybrid Neural Networks

18. Neuromorphic Computing

19. Quantum Computing

20. Answers to the Questions

21. Other Books You May Enjoy

22. Index

CRLMM applied to an automated apparel manufacturing process

With an automated planning and scheduling system, not an advanced planning and scheduling system, Amazon has brought apparel manufacturing closer to the consumer.

Artificial intelligence will boost existing processes. In this section, an RL-DL-CRLMM system will optimize an apparel manufacturing process.

An apparel manufacturing process

Amazon's apparel manufacturing patent can be summarized as follows:

P1: Grouping apparel customer orders by products and sizes. This process has been around since the origins of industrial apparel manufacturing centuries ago.
P2: Automatically cutting lays. A lay is a stack of pieces of cloth. It is like cutting a circle in a stack (lay) of several pieces of paper at the same time.
P3: Moving the packs of the parts of clothing to the assembly lines on conveyor belts (see Chapter 10, Conceptual Representation Learning).
P4: Other operations depending...