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.
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.
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.
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.
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
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.
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.
From Build an Orchestrator in Go by Tim Boring
This article covers
The evolution of application deployments
Classifying the components of an orchestration system
From Graph-Powered Machine Learning by Alessandro Negro
This article discusses managing data in graph-powered machine learning projects.
From Parallel and High-Performance Computing by Robert Robey and Yuliana Zamora
This article takes a deep dive into GPUs.