Tag

algorithms

Going Inside Machine Learning and Deep Learning Algorithms

If you want to excel in ML and deep learning, you need to know more than how to implement the algorithms—you need to know them inside-out. This book delves into selected algorithms and teaches you how to build your own from scratch.

Learning C# by Doing Tiny Projects

With Tiny C# Projects by Denis Panjuta and Jafar Jabbarzadeh

Want to learn C#? There’s no better way to learn than by practical application. This book teaches C# via fun, real-world projects. You’ll be writing C# in no time!

Read on to learn more.

Learning R Using NBA Statistics

With the Statistics Playbook by Gary Sutton

This book will teach you how to use R in a different way than any other book out there. You will approach R concepts using publicly-available NBA statistical data rather than prepared datasets, and learn how to combine various methods and techniques.

Read on to learn more.

What is Cryptography?

An excerpt from Secret Key Cryptography by Frank Rubin

This article covers:

•       Basic terms used in cryptography

•       What is an unbreakable cipher?

•       What are the different types of cryptography?

Read it if you’re interested in cryptography.

The Cryptographer’s Toolbox

From Secret Key Cryptography by Frank Rubin

This article covers:

·  The rating system used for ciphers

·  Substitution ciphers

·  Transposition ciphers

·  Fractionation, breaking letters into smaller units

·  Pseudorandom number generators

Collective Communication Pattern: Improving Performance When Parameter Servers Become a Bottleneck

From Distributed Machine Learning Patterns by Yuan Tang

In this article, we introduce the collective communication pattern, which is a great alternative to parameter servers when the machine learning model we are building is not too large without having to tune the ratio between the number of workers and parameter servers.

Parameter Server Pattern: Tagging Entities in 8 Millions of YouTube Videos

From Distributed Machine Learning Patterns by Yuan Tang

In this article, we introduce the parameter server pattern which comes handy for situations where the model is too large to fit in a single machine such as one we would have to build for tagging entities in the 8 millions of YouTube videos.

Components of an Orchestrator

From Build an Orchestrator in Go by Tim Boring

This article covers

The evolution of application deployments
Classifying the components of an orchestration system

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.

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