Before You Model: planning and scoping

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.

Interview with Brian Goetz

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)

Sharpen your Java and compsci skills

From Classic Computer Science Problems in Java by David Kopec

Using AI to Get Business Results

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.

Transparent and understandable AI systems

From Interpretable AI by Ajay Thampi

Gathering Data at Scale for Real-World AI

From AI as a Service by Peter Elger and Eóin Shanaghy

This article discusses gathering data for real-world AI projects and platforms.

Applying AI to Existing Platforms

From AI as a Service by Peter Elger and Eóin Shanaghy

This article discusses how to add AI to existing platforms.


The Ultimate Speed Reader

Why speed read this, you ask? Learn how AI can plow through an inbox at superhuman speeds. Let an AI summarize and help you focus. That’s what I need. [ed. This is my first joint blog post with Chris Mattmann,… Continue Reading →

Evolutionary Algorithms: genetic algorithms

From Grokking Artificial Intelligence Algorithms by Rishal Hurbans

What you’ll learn in this article:

§ The lifecycle of a genetic algorithm.

§ Designing and developing a genetic algorithm to solve problems.

§ The parameters for configuring a genetic algorithm lifecycle based on different scenarios, problems, and data sets.

Delivering the Right Search Results

From AI-Powered Search by Trey Grainger

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