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

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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

Preface

This second edition of Artificial Intelligence By Example will take you through the main aspects of present-day artificial intelligence (AI) and beyond!

This book contains many revisions and additions to the key aspects of AI described in the first edition:

The theory of machine learning and deep learning including hybrid and ensemble algorithms.
Mathematical representations of the main AI algorithms including natural language explanations making them easier to understand.
Real-life case studies taking the reader inside the heart of e-commerce: manufacturing, services, warehouses, and delivery.
Introducing AI solutions that combine IoT, convolutional neural networks (CNN), and Markov decision process (MDP).
Many open source Python programs with a special focus on the new features of TensorFlow 2.x, TensorBoard, and Keras. Many modules are used, such as scikit-learn, pandas, and more.
Cloud platforms: Google Colaboratory with its free VM, Google Translate, Google Dialogflow, IBM Q for quantum computing, and more.
Use of the power of restricted Boltzmann machines (RBM) and principal component analysis (PCA) to generate data to create a meaningful chatbot.
Solutions to compensate for the emotional deficiencies of chatbots.
Genetic algorithms, which run faster than classical algorithms in specific cases, and genetic algorithms used in a hybrid deep learning neural network.
Neuromorphic computing, which reproduces our brain activity with models of selective spiking ensembles of neurons in models that reproduce our biological reactions.
Quantum computing, which will take you deep into the tremendous calculation power of qubits and cognitive representation experiments.

This second edition of Artificial Intelligence By Example will take you to the cutting edge of AI and beyond with innovations that improve existing solutions. This book will make you a key asset not only as an AI specialist but a visionary. You will discover how to improve your AI skills as a consultant, developer, professor, a curious mind, or any person involved in artificial intelligence.