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Artificial Intelligence By Example

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

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839211539
Length 578 pages
Edition 2nd Edition
Languages
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Toc

Table of Contents (23) Chapters Close

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

Building the RL-DL-CRLMM

The full code of the RL-DL-CRLMM program is RL_DL.py. It is built on the knowledge and programs of the previous chapters and previous sections of this chapter.

The RL-DL-CRLMM contains three components:

  • A CRLMM convolutional network that will analyze each frame it receives from the webcam that is located right over the pieces of garment packs on the conveyor belt coming from the cutting section.
  • An optimizer using a modified version of the Z(X) described previously that plans how the assembly stations will be loaded in real-time.
  • An MDP that will receive the input of the optimizer function and schedule the work of the assembly stations. It also produces the modified Z(X) updated value of the weights of each assembly station for the next frame.

In the physical world, the conveyor belt transports the garment packs, a picture (frame) is taken every n seconds, and the RL-DL-CRLMM runs. The output of the RL-DL-CRLMM sends...

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