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.

Exploring the useEffect API with Easy Examples

From React Hooks in Action by John Larsen

Some of our React components are super-friendly, reaching out to say “hi” to APIs and services outside of React. Although they’re eternally optimistic and like to think the best of all those they meet, there are some safeguards to be followed. In this article, we’ll look at setting up side effects in ways that won’t get out of hand. In particular, we’ll explore these four scenarios:

§ Running side effects after every render

§ Running an effect only when a component mounts

§ Cleaning up side effects by returning a function

§ Controlling when an effect runs by specifying dependencies

To focus on the API we’ll create some easy component examples. First up, let’s say “Bonjour, les side-effects.”

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 →

OWASP API Security Top 10

From Microservices Security in Action by Prabath Siriwardena

This article explores the OWASP API top-ten list of API security vulnerabilities.

What is Functional Programming?

From Functional Programming in Kotlin by Marco Vermeulen

This article discusses what functional programming is (and is not), using Kotlin for examples.

Introduction to Azure Storage

Introduction to Azure Storage

From Learn Azure in a Month of Lunches, Second Edition by Iain Foulds

This article delves into Azure storage.

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.

Introducing Mock Frameworks

From JUnit in Action, Third Edition by Catalin Tudose

This article discusses widely-used mock frameworks such as EasyMock, JMock, and Mockito.

Reliability through Self-Conscious Code

From Seriously Good Software by Marco Faella

This article delves into how thinking about what you want your code to do before you write it can lead to more reliable code.

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