awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems View the Project on GitHub View On GitHub An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to
DuckDuckGo and Bing are not true alternatives – they’re just worse versions of Google. The next Google can’t just be an input box that spits out links. We need new thinking to create something much better than what came before. In the last few years, different groups of people came to the same conclusion, and started working on the next generation of search engines. For this new generation, privac
In this series, we look at the most loved languages according to the Stack Overflow developer survey, the spread and use cases for each of them and collect some essential links on how to get into them. First up: Rust. IntroDespite its relatively tiny userbase—roughly 5% of programmers use it—Rust has consistently come in number one as the most loved language in our developer survey for the past fe
Today, we are excited to announce the launch of .NET 9, the most productive, modern, secure, intelligent, and performant release of .NET yet. It’s the result of another year of effort on the part of thousands of developers from around the world. This new release includes thousands of performance, security, and functional improvements. You will find sweeping enhancements across the entire .NET stac
In the Stack overflow 2020 survey, Rust was picked as #1 most loved programming language, thanks to 86% of developers who said they would continue using it. For the language creators, this is nothing new – Rust has been winning the survey ever since 2016. On Tiobe Index, Rust is rising in popularity as well – achieving #18 positions among the most popular languages in September. It also didn’t fai
Like almost any question about AI, “How does AI impact software architecture?” has two sides to it: how AI changes the practice of software architecture and how AI changes the things we architect. These questions are coupled; one can’t really be discussed without the other. But to jump to the conclusion, we can say that AI hasn’t had a big effect on the practice of software architecture, and it ma
Overview A. Math Review 1. Tensors and Shapes B. Machine Learning 2. Introduction to Machine Learning 3. Regression & Model Assessment 4. Classification 5. Kernel Learning C. Deep Learning 6. Deep Learning Overview 7. Standard Layers 8. Graph Neural Networks 9. Input Data & Equivariances 10. Equivariant Neural Networks 11. Explaining Predictions 12. Attention Layers 13. Deep Learning on Sequences
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The Next Google
Getting started with ... Rust - Stack Overflow
Announcing .NET 9 - .NET Blog
5 Reasons Why Rust Is The Future
Software Architecture in an AI World
Overview — deep learning for molecules & materials