Search Results for "deep"

...The course is carefully designed with a structured catalog, vivid and approachable language, and an engaging style that avoids the dry and mechanical tone of many technical books. It covers the basics of Rust, such as ownership, borrowing, lifetimes, traits, and generics, but also dives deep into advanced topics like performance optimization, linked list implementations, async programming with Tokio, standard library internals, Cargo usage, and WebAssembly development. The project emphasizes practical learning through exercises, helping users approach Rust study as if it were a university course. It also provides a "Cookbook" section of practical code snippets for common tasks such as file operations, regex handling, and database interactions, allowing learners to quickly reference solutions without searching externally.

DeepLearning-500-questions is a comprehensive handbook that compiles 500 important questions on deep learning, curated to serve as a valuable reference for AI engineer interviews and self-study. Edited by Tan Jiyong with contributions from Guo Zizhao, Li Jian, and Dian Songyi, the book systematically covers both theoretical foundations and practical applications of deep learning. The first sections focus on essential mathematics, machine learning basics, and deep learning foundations, establishing the groundwork for more advanced topics. ...

...The project uses a simple shopping-cart application written in JavaScript and React/Redux to illustrate how code evolves from “bad” via “better” to “good” across those three dimensions. By examining common smells—poor naming, deep nesting, long functions, tight coupling—readers learn how to restructure code to improve maintainability. It is targeted at developers of any experience level, though beginners will find its concrete examples especially useful. The tutorial-style repository includes code with comments and comparisons between less readable and more readable versions, promoting intentional design.