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

Hybrid Artificial Intelligence

You will enjoy working with short program examples for data manipulation, deep learning, natural language processing, probabilistic programming, knowledge representation, semantic web, and linked data.

Mark Watson

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About the Book

The tutorial material starts with a review AI topics with background information. We will then proceed to material on Python development, getting you setup for the later cookbook style examples.

We will cover Deep Learning, old fashioned symbolic AI, broad coverage of data sources as well as wide range of tups and techniques for using Python both in experiments and in production.

The author has been a general AI practitioner since 1982, developed neural network products and projects since 1986, and deep learning since 2015.

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About the Author

Mark Watson

Mark Watson is a consultant specializing in LLMs, deep learning, machine learning, knowledge graphs, and general artificial intelligence software development. He uses Common Lisp, Clojure, Python, Java, Haskell, and Ruby for development.

He is the author of 20+ published books on Artificial Intelligence, Deep Learning, Java, Ruby, Machine Learning, Common LISP, Clojure, JavaScript, Semantic Web, NLP, C++, Linux, and Scheme. He has 55 US Patents.

Mark's consulting customer list includes: Google, Capital One, Olive AI, CompassLabs, Disney, Sitescout.com, Embed.ly, and Webmind Corporation.

Mark wrote ten traditional published books for McGraw Hill, Springer Verlag, J Wiley, and Morgan Kaufman publishers before adopting the LeanPub self-publishing platform.

Episode 253

An Interview with Mark Watson

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