Gentle introductions to AI, ML, and DI

Recently, a colleague asked me for some layman introductions to AI and machine learning.  He’s on the road and in a bit of a hurry, so I put together a few online resources.  A neat trick: read free introductory Kindle chapters at Amazon, or download samples to your device. Here’s what I recommended:

  • AI: Artificial Intelligence: A Modern Approach (read starting with the introduction here). I think of Norvig as a father of the field.
  • Machine learning: Machine Learning by Peter Flash (read the prologue that you can find here).
  • Transfer: Learning to Learn, by me and Sebastian Thrun (read the two pages on transfer here)
  • Deep Learning: The next generation of neural networks a great talk by Geoff Hinton at Google.  Also see this book chapter (by Bengio, Goodfellow, and Courville) for an up-to-date (still in draft) review of where we’re at today, including how these multiple topics relate.
  • Decision Intelligence: If you go to this blog’s front page and click “Sign up now!”, you’ll receive a free copy of my ebook: Decision Intelligence: A Primer.  This post explains how machine learning connects to Decision Intelligence.  This video of my presentation at CMU describes how DI evolved from ML. And here is a video series about DI that I put together.

If you choose to dive more deeply, and build a learner reasonably painlessly yourself, I do like Machine Learning with R, which is a practical, step-by-step approach to using the open-source R package (easy to download and install to PCs or Macs).  A similarly accessible book is Machine Learning for Hackers. It also uses R, with a focus on text processing.

R is amazing, and hands-down the easiest way to get started in machine learning. Click To Tweet

Do you have any favorite resources?  Please suggest them in the comments, thank you!

Lorien Pratt

Pratt has been delivering AI and DI solutions for her clients for over 30 years. These include the Human Genome Project, the Colorado Bureau of Investigation, the US Department of Energy, and the Administrative Office of the US Courts. Formerly a computer science professor, Pratt is a popular international speaker and has given two TEDx talks. Her Quantellia team offers AI, DI, and full-stack software solutions to clients worldwide. Previously a leading technology analyst, Pratt has also authored dozens of academic papers, co-edited the book: Learning to Learn, and co-authored the Decision Engineering Primer. Her next book: Link: How Decision Intelligence makes the Invisible Visible (Emerald Press), is in production. With media appearances such as on TechEmergence and GigaOm, Pratt is also listed on the Women Inventors and Innovator’s Mural. Pratt blogs at www.lorienpratt.com.

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