About the Book
Github repository update: December 2020: all examples are also provided in Python (the book only covers the Hy language versions of the examples).
Updated July 31, 2020: I corrected several typos, added more descriptive text, fixed a possible installation problem for the NLP coreference example, and did some rework on the semantic web material (knowledge Graphs).
Updated June 7, 2020: I added two chapters on using the Bing Search APIs and on my Knowledge Graph Navigator project. Several other minor changes.
While this is a book on the Hy Lisp language,
In addition to being a tutorial and cookbook on using the Hy language, longer examples explore a variety of different applications and tools. The current structure of the book is:
- Introduction to the Hy Language
- Why use Lisp? Advantages of bottom up development using macros and closures
- Relational databases
- Web app development
- Web scraping
- Using the Bing search APIs
- Accessing semantic web and linked data sources like Wikipedia, DBpedia, and Wikidata
- Automatically constructing Knowledge Graphs from text documents, semantic web and linked data
- Deep Learning (predictive model from spreadsheet data and a LSTM-based English text language model)
- Natural Language Processing (NLP) using Deep Learning
- Creating Knowledge Graphs from text data
- Hy language implementation of the author's Knowledge Graph Navigator project
About the Author
Mark Watson a consultant specializing in deep learning, machine learning, knowledge graphs, and general artificial intelligence software development. He uses Python, Common Lisp, Java, Clojure, Haskell, and Ruby for development.
Mark's consulting customer list includes: Google, Capital One, Olive AI, CompassLabs, Disney, Sitescout.com, Embed.ly, and Webmind Corporation.
web site: https://markwatson.com/