Managing Data Sources in Machine Learning

From Graph-Powered Machine Learning by Alessandro Negro

This article discusses managing data in graph-powered machine learning projects.

Getting to Know GPUs

From Parallel and High-Performance Computing by Robert Robey and Yuliana Zamora

This article takes a deep dive into GPUs.

Creating a Bipartite Graph for a User-Item Dataset

By Graph-Powered Machine Learning Alessandro Negro

This article discusses creating a bigraph for a user-item dataset.

Genetic algorithms: Biologically inspired, fast-converging optimization

Take 40% off Advanced Algorithms and Data Structures by entering fcclarocca into the discount code box at checkout at manning.com. This article covers Introducing the genetic algorithm Examining whether genetic algorithms are better than simulated annealing Solving the “Packing to… Continue Reading →

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)

Techniques for handling modern big data applications

From Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic

All About Bloom Filters

From Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic

This article covers:

·  Learning what Bloom filters are, why and when they are useful

·  Understanding how Bloom filters work

·  Configuring a Bloom filter in a practical setting

·  Exploring the interplay between Bloom filter parameters

Sharpen your Java and compsci skills

From Classic Computer Science Problems in Java by David Kopec

Transparent and understandable AI systems

From Interpretable AI by Ajay Thampi

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.

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