Command Line Rust
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Command-line Rust
For several consecutive years, Rust has been voted "most loved programming language" in Stack Overflow's annual developer survey. This open source systems programming language is now used for everything from game engines and operating systems to browser components and virtual reality simulation engines. But Rust is also an incredibly complex language with a notoriously difficult learning curve. Rather than focusing on the language as a whole, this guide teaches Rust using a single small, complete, focused program in each chapter. Author Ken Youens-Clark shows you how to start, write, and test each of these programs to create a finished product. You'll learn how to handle errors in Rust, read and write files, and use regular expressions, Rust types, structs, and more. Discover how to: Use Rust's standard libraries and data types such as numbers, strings, vectors, structs, Options, and Results to create command-line programs Write and test Rust programs and functions Read and write files, including stdin, stdout, and stderr Document and validate command-line arguments Write programs that fail gracefully Parse raw and delimited text manually, using regular expressions and Rust crates Use and control randomness
Rust High Performance
Author: Iban Eguia Moraza
language: en
Publisher: Packt Publishing Ltd
Release Date: 2018-03-28
Find bottlenecks, identify the proper algorithm to use, optimize performance, and create really efficient Rust applications Key Features Understand common performance pitfalls and improve the performance of your applications. Get to grips with parallel programming and multithreading with Rust. Learn metaprogramming in Rust. Book Description At times, it is difficult to get the best performance out of Rust. This book teaches you to optimize the speed of your Rust code to the level of languages such as C/C++. You'll understand and fix common pitfalls, learn how to improve your productivity by using metaprogramming, and speed up your code by concurrently executing parts of it safely and easily. You will master the features of the language which will make you stand out and use them to really improve the efficiency of your algorithms The book begins with a gentle introduction to help you identify bottlenecks when programming in Rust. We highlight common performance pitfalls, along with strategies to detect and resolve these issues early. We move on to mastering Rust's type system, which will enable us to create impressive optimizations in both performance and safety at compile time. You will then learn how to effectively manage memory in Rust, mastering the borrow checker. We move on to measuring performance and you will see how this affects the way you write code. Moving ahead, you will perform metaprogramming in Rust to boost the performance of your code and your productivity. You will finally learn parallel programming in Rust, which enables efficient and faster execution by using multithreading and asynchronous programming. What you will learn Master tips and tricks to make your code faster. Learn how to identify bottlenecks in your Rust applications Discover how to profile your Rust software. Understand the type system to create compile-time optimizations. Master the borrow checker . Learn metaprogramming in Rust to avoid boilerplate code. Discover multithreading and work stealing in Rust. Understand asynchronous programming in Rust. Who this book is for This book is for Rust developers keen to improve the speed of their code or simply to take their skills to the next level.
Implementing MLOps in the Enterprise
Author: Yaron Haviv
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-11-30
With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy