Search Results for "code coverage"

Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter...

Python Tutorial is a Chinese beginner-friendly Python tutorial repository focused on practical self-study. It is written for learners who want to build programming fundamentals step by step instead of collecting scattered resources without a path. The course is based on Python 3.10+ and marks newer language features from Python 3.11, 3.12, and 3.13 where relevant. It offers both a document-style reading site and an interactive learning site where users can write code in the browser. The...

The Ultimate Python Course is a structured learning repository designed to take programmers from Python fundamentals to more advanced concepts. Its chapters cover modules, package management, variables, data types, strings, collections, conditionals, loops, functions, recursion, and file handling. Later sections introduce object-oriented programming, inheritance, polymorphism, type hints, virtual environments, lambda functions, and functional programming tools. Each chapter is accompanied by...

ThinkPython2 is the repository for the second edition of Allen Downey’s Think Python textbook, which teaches programming fundamentals in Python to beginners. The code includes all of the example programs, exercises, and supplementary files referenced in the book, allowing learners to run the examples, experiment, and extend them. The repository contains clean, well-commented Python scripts that are easy to follow and map directly to chapters of the text, covering topics like variables,...

pytorch-tutorial is a highly popular educational repository that teaches deep learning with PyTorch through step-by-step examples and well-structured lessons. It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer...

Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,...