From Automated Machine Learning in Action by Qingquan Song, Haifeng Jin, and Xia Hu
This article covers
• Defining and introducing the fundamental concepts of machine learning
• Describing the motivation for and high-level concepts of automated machine learning
In case you missed it, here is Peter Elger and Eoin Chanaghy’s live Twitch coding stream recap. For more, check out the book: AI as a Service. For more live coding streams, subscribe to Manning’s Twitch channel here: https://www.twitch.tv/manningpublications
From Machine Learning Engineering in Action by Ben Wilson
Before we get into how successful planning phases for ML projects are undertaken, let’s go through a simulation of the genesis of a typical project at a company that doesn’t have an established or proven process for initiating ML work.
Brian Goetz is one of the leading figures in the Java world. As Java Language Architect at Oracle, he helps steer the direction of the language’s evolution and its supporting libraries. He has led the language through several important modernizations, including Project Lambda. Brian has a long career in software engineering and is the author of the best-selling book “Java Concurrency in Practice.” (Addison-Wesley, 2006)
From Classic Computer Science Problems in Java by David Kopec
From Succeeding with AI by Veljko Krunic
This article discusses how to get practical business results from AI and how this book will help you learn how to do it.
From Interpretable AI by Ajay Thampi
From AI as a Service by Peter Elger and Eóin Shanaghy
This article discusses gathering data for real-world AI projects and platforms.
| From AI as a Service by Peter Elger and Eóin Shanaghy
This article discusses how to add AI to existing platforms. |
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