Search Results for "code coverage" - Page 8
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Showing 314 open source projects for "code coverage"
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Pattern Recognition and Machine Learning
Repository of notes, code and notebooks in Python
Pattern Recognition and Machine Learning is an open-source repository that provides Python implementations and interactive notebooks for algorithms presented in the book Pattern Recognition and Machine Learning by Christopher Bishop. The project recreates many of the mathematical concepts and diagrams from the book using executable Jupyter notebooks, allowing readers to experiment directly with the algorithms described in the text. Each section of the repository corresponds to chapters in... -
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ISLR-python
An Introduction to Statistical Learning
ISLR-python is an educational repository that provides Python implementations and notebooks corresponding to examples and exercises from the book An Introduction to Statistical Learning. The project recreates tables, figures, and laboratory exercises originally presented in the book so that readers can explore the concepts using Python rather than the original R environment. The repository includes Jupyter notebooks demonstrating statistical learning methods such as linear regression,... -
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P/Invoke
A library containing all P/Invoke code so you don't have to import it
A library containing all P/Invoke code so you don't have to import it every time. Maintained and updated to support the latest Windows OS. A collection of libraries intended to contain all P/Invoke method signatures for popular operating systems. Think of it as https://pinvoke.net, but proven to compile and work properly, and often with sample usage in the form of unit tests. A unique C# project wraps each native library. The C# project may multi-target in order to support many versions of... -
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Monix
Asynchronous, Reactive Programming for Scala and Scala.js
Monix is a high-performance, reactive, and asynchronous programming library for Scala and Scala.js. Built as a Typelevel project, it provides advanced abstractions like Task, Observable, Iterant, and Coeval, enabling compositional, back-pressure‑aware event-driven systems that integrate cleanly with Cats Effect and Reactive Streams. -
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Tech Interview Handbook
Curated coding interview preparation materials
Tech Interview Handbook is a curated, mostly self-contained compilation of technical interview preparation resources—including algorithms, system design, resume tips, and behavioral questions—crafted for busy software engineers. The information in this repository is condensed. Ultimately, the key to succeeding in technical interviews is consistent practice and I don't want to bore you with too many words. I tell you the minimum you need to know on how to go about navigating the interview... -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases,... -
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LeetCode
LeetCode Problems' Solutions
LeetCode is a long-running repository of solutions to LeetCode programming problems. It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how... -
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PyTorch Handbook
The pytorch handbook is an open source book
PyTorch Handbook is an open-source educational project designed to help developers and researchers quickly learn deep learning using the PyTorch framework. The repository functions as an online handbook that explains how to build, train, and evaluate neural network models using PyTorch. It includes tutorials and examples that demonstrate common deep learning tasks such as image classification, neural network design, model training workflows, and evaluation techniques. The material is written... -
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Functional-Light JavaScript
Pragmatic, balanced FP in JavaScript
Functional-Light JavaScript is an online book that teaches functional programming principles through a pragmatic JavaScript lens. Instead of insisting on strict purity, it adopts a balanced approach that keeps code practical while showing how immutability, composition, and declarative thinking improve quality. Chapters build up from values and closures to higher-order functions, list operations, transducing, and async patterns, all grounded in idiomatic JS. The writing favors intuition and... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Fira Code
Free monospaced font with programming ligatures
Fira Code is a free and open source monospaced font containing programming ligatures for the most commonly-used multi-character combinations in programming. Programmers use a lot of symbols that are encoded through a series of characters. Often these symbols are quickly done and overlooked, causing errors due to spacing, etc. Fira Code helps solve such problems. While all programming languages should be designed with full-fledged Unicode symbols for operators, such is not yet the case. Until... -
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go-fundamental-programming
Set of video and voice tutorials for the Go language
go-fundamental-programming is the code and notes repository for the Chinese video course, a foundational Go programming tutorial aimed at beginners. The author positions it explicitly as a way to share the knowledge and pitfalls accumulated while learning Go, so that new learners can avoid common mistakes and weird corner cases. The course is delivered as a series of lectures, and each lecture has a dedicated lectureX.md file that serves as classroom notes, listing the knowledge points... -
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Deeplearning.ai
Study notes, summaries, and auxiliary materials for deep learning
Deeplearning.ai collects study notes, summaries, and auxiliary materials aligned with the popular deep learning course series many learners take early in their AI journey. It distills core ideas such as optimization, regularization, convolutional networks, sequence models, and practical training tricks. The explanations aim to bridge theory and practice, often connecting mathematical intuition to code-level implications. By organizing the content as “books” or structured notes, it gives... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes... -
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Modern C++ Template
A template for modern C++ projects using CMake, Clang-Format
...Doxygen support, through the ENABLE_DOXYGEN option, which you can enable if you wish to use it. Unit testing support, through GoogleTest (with an option to enable GoogleMock) or Catch2. Code coverage, enabled by using the ENABLE_CODE_COVERAGE op. -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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Machine Learning & Deep Learning
machine learning and deep learning tutorials, articles
Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification,... -
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REACT COOL STARTER
A starter boilerplate for a universal web app
A simple but feature-rich starter boilerplate for creating your own universal app. It built on the top of React, Redux, React Router and Express. Includes all the hot stuff and modern web development tools such as Redux Toolkit, TypeScript, Webpack, Babel, PostCSS, React Refresh, Jest and React Testing Library. See the “Features” section for other awesome features you can expect. They're several React frameworks today, however this is a DIY-oriented start-kit. It shows you how to build a... -
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OpenCover
Code coverage tool for .NET 2 and above
OpenCover is a free and open source code coverage tool for .NET 2 and above (Windows OSs only - no MONO), with support for 32 and 64 processes and covers both branch and sequence points. It uses the profiler API that is currently only available to .NET Frameworks running on the Windows platform. OpenCover is an attempt at building a code coverage utility that addresses certain issues in maintaining PartCover support for 64-bit processes. -
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Jacoco Android Gradle Plugin
Gradle plugin that creates JaCoCo test reports for Android unit tests
A Gradle plugin that auto-creates and configures JaCoCo code coverage tasks for each Android app/module variant, saving you from manual setup across build types and flavors. -
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Vue.js Analysis
Vue.js source code analysis
Vue.js Analysis is an open-source Chinese ebook and companion learning resource that analyzes the Vue.js source code in depth. It was created to help learners understand Vue’s implementation principles in a more systematic way than scattered blog posts. The project focuses on Vue 2.x internals, including initialization, reactivity, virtual DOM, component rendering, template compilation, lifecycle behavior, and related architectural ideas. It is connected to a paid video course but keeps the... -
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ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design
The ml-design-patterns repository contains the source code and examples that accompany the book “Machine Learning Design Patterns,” providing practical implementations of reusable solutions for common challenges in machine learning systems. It organizes patterns into categories such as data representation, problem framing, and model training, helping practitioners understand how to structure ML pipelines effectively. The repository includes implementations of techniques like feature hashing,... -
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sc
Common libraries and data structures for C
...There is no build for libraries, just copy files you want. e.g If you want the logger, copy sc_log.h and sc_log.c to your project. High performance & minimal memory usage. Portability between many operating systems and architectures. Tests with 100% branch coverage and multiple sanitizers. Drag & drop source code distribution. There is 100% branch coverage on Linux. Buffer for encoding/decoding variables, best fit for protocol/serialization implementations. Signal safe snprintf & Signal handler (handling CTRL+C, printing backtrace on crash etc). I often use these libraries for high-performance server-side applications. ... -
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Machine Learning Beginner
Machine Learning Beginner Public Account Works
Machine Learning Beginner targets newcomers who are just getting started with machine learning and need a gentle, guided path. It introduces the core vocabulary and the mental map of supervised and unsupervised learning before moving into simple algorithms. The materials prioritize conceptual clarity, then progressively add code to solidify understanding. Step-by-step examples help learners see how data preparation, model training, evaluation, and iteration fit together. Because the scope is... -
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jstutorial
Javascript tutorial book
This repository is a comprehensive, tutorial-style guide to JavaScript that walks readers from the language’s fundamentals to practical application in the browser and on the server. It explains core concepts like values and types, scope, functions, objects, and prototypes in a clear, example-driven style that favors short, readable snippets. The material steadily introduces modern features—modules, arrow functions, classes, destructuring, promises, and async/await—while relating them back to... -
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R4DS (R for Data Science)
R for data science: a book
...The repository contains the source files (Quarto / RMarkdown), example datasets, visualizations, exercises, and all content needed to build the book. Includes many example datasets, diagrams, code samples, and “hands-on” exercises. Comprehensive coverage of data-science workflow: data import, cleaning, transformation, exploration, modelling etc. Includes topics beyond basics: relational data (joins), date/time, strings, working with missing values, visualizing data, etc.
