Artificial Intelligence Programming in Python: Exploring the Boundaries of Deep Learning, Symbolic AI, and Knowledge Representation

Mark Watson

Table of Contents

Artificial Intelligence Programming in Python: Exploring the Boundaries of Deep Learning, Symbolic AI, and Knowledge Representation

Cover Material, Copyright, and License
- This book is licensed with Creative Commons Attribution CC BY Version 3 That Allows Reuse In Derived Works
Preface
Part I - A Brief Introduction to AI and Effectively Using Python
An Introduction to Artificial Intelligence
Python Tips and Techniques
Ethics and Human Values
Part II - Machine Learning and Deep Learning
(Almost) Everything You Really Need To Know About Machine Learning
- Introduction to Supervised and Unsupervised Learning
- Feature Engineering
Tensoflow and Keras Model for Wisconsin Cancer Data Set
- Jupyter Notebook
Using TensorFlow for Implementing Deep Neural Networks
Generating Images With Deep Learning
Part III - Natural Language Processing
Introduction to Natural Language Processing
Entity Detection
Text Generation
Part IV - Knowledge Representation Using Semantic Web Technologies
Knowledge Representation Using the Neo4J Graph Database
Linked Data and the Semantic Web
Knowledge Graph Creator
Knowledge Graph Navigator
DBPedia Question Answering System Using SparQL and Deep Learning
Part V - GOFAI - Good Old Fashioned Symbolic Artificial Intelligence
Part VI - Hybrid Symbolic and Deep Learning Approaches to Artificial Intelligence
Part VII - Miscellaneous Code and Techniques
Using the Microsoft Bing Search APIs
Responsible Web Scraping
Displaying Graph Data Using PyGraphViz
Introduction to Programming Quantum Computing
Book Wrap Up
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