Subject

Articles

The Ambient Context Anti-Pattern

From Dependency Injection, Principles, Practices, and Patterns by Steven van Deursen and Mark Seemann

This article explores the Ambient Context DI anti-pattern: what it is, how to identify it, and why it’s so dangerous.

The Service Locator Anti-Pattern

From Dependency Injection, Principles, Practices, and Patterns by Steven van Deursen and Mark Seemann

This articles explains the Service Locator anti-pattern: what it is, what effects it has on code, and why it’s a problem.

Understanding Method Injection

From Dependency Injection, Principles, Practices, and Patterns by Steven van Deursen and Mark Seemann

This article delves into the Method Injection DI Pattern: how it works, and when and why you might want to use it.

Understanding Constructor Injection

From Dependency Injection, Principles, Practices, and Patterns by Steven van Deursen and Mark Seemann

This article delves into the Constructor Injection DI pattern—what it is and how, when, and why to use it.

Models as a Tool for Deeper Insight

By Dan Bergh Johnsson, Daniel Deogun, and Daniel Sawano

This article delves into DDD and models: what they are, how they relate, and how models work within Domain-Driven Design.

The Random Cut Forest Algorithm

From Machine Learning for Business by Doug Hudgeon and Richard Nichol

In this article, you’ll see how SageMaker and the Random Cut Forest algorithm can be used to create a model that will highlight the invoice lines that Brett should query with the law firm. The result will be a repeatable process that Brett can apply to every invoice that will keep the lawyers working for his bank on their toes and will save the bank hundreds of thousands of dollars per year. Off we go!

Building Linear Models with Dask ML

From Data Science at Scale with Python and Dask by Jesse C. Daniel

This article delves into building linear models using Dask-ML.

Istio Gateway

From Istio in Action by Christian Posta

This article explores the Istio gateway.

Handling Data with R

From Practical Data Science with R, 2nd Ed. By Nina Zumel and John Mount

In this article, we demonstrate some ways to get to know your data, and discuss some of the potential issues that you’re looking for as you explore.

Ingesting Data from Files with Spark, Part 4

From Spark in Action, 2nd Ed. by Jean Georges Perrin

This is the last in a series of 4 articles on the topic of ingesting data from files with Spark. This section deals with ingesting a TXT file.

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