Search Results for "code coverage" - Page 8
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Showing 280 open source projects for "code coverage"
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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... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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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. -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates... -
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DeepCode for Visual Studio Code
DeepCode extension for Visual Studio Code
...DeepCode AI powers Snyk's one-click security fixes and comprehensive app coverage, letting developers build fast while staying secure. Our specialized DeepCode AI is built and refined by top-tier researchers that use training data from millions of open source projects, never customer data. DeepCode AI's hybrid approach uses multiple models and security-specific training sets for one purpose, to secure applications. -
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CyC2018.github.io
Personal knowledge site built with GitHub Pages
This is a personal knowledge site built with GitHub Pages, organizing computer science notes and study materials in a browsable format. It aggregates content across algorithms, data structures, networking, operating systems, databases, and interview preparation into a coherent index. The presentation emphasizes succinct explanations paired with diagrams, tables, or code snippets to speed recall. Because the site is generated from a repository, it benefits from issue tracking, pull requests,... -
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Nebula-Python-SDK
A python SDK for managing Nebula container orchestrator
A python SDK for managing Nebula container orchestrator. First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free.... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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BigchainDB Server
Meet BigchainDB. The blockchain database
BigchainDB is the blockchain database. This repository is for the BigchainDB Server. Running and testing the latest version of the BigchainDB Server is easy. Make sure you have a recent version of Docker Compose installed. -
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Intermock
Mocking library to create mock objects with fake data for TypeScript
...By leveraging Intermock, developers can quickly generate realistic mock datasets for testing, prototyping, and documentation purposes without writing boilerplate code. -
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SentEval
A python tool for evaluating the quality of sentence embeddings
SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic... -
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Redux-ORM
A small, simple and immutable ORM to manage relational data
...All queries are lazily evaluated and come with built-in support for memorization. It provides a clean abstraction over low-level updates, protecting the state from accidental mutations. With nearly 100% branch coverage, the library is thoroughly tested to ensure rock-solid code quality. No matter where your data comes from, Redux-ORM will stay out of its way. Even a custom database layer is possible. Defining fields on a Model specifies the table structure in the database for that Model. In order to generate a description of the whole database's structure, we need a central place to register all Models we want to use. ... -
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Stable Baselines
A fork of OpenAI Baselines, implementations of reinforcement learning
Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a detailed presentation of Stable Baselines in the Medium article. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around which new ideas can be added, and as a tool for comparing a new... -
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American Fuzzy Lop
American fuzzy lop - a security-oriented fuzzer
AFL (American Fuzzy Lop) is a widely used graybox fuzzer that discovers bugs by mutating inputs and steering execution using lightweight instrumentation. Instead of random mutations alone, it uses coverage feedback to evolve input corpora, pushing programs into deeper and more interesting code paths. Its workflow emphasizes quick start: point it at a target binary with compile-time instrumentation (or use QEMU-based mode when recompilation isn’t possible), seed it with a small corpus, and let it iterate. AFL is known for finding serious security issues in complex software due to its corpus minimization, queue management, and deterministic mutation stages that balance breadth and depth. ... -
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Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
Reliable Fidelity and Diversity Metrics for Generative Models (ICML 2020). Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fréchet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the generated images, recent papers have introduced variants of precision and recall metrics to diagnose those... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
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... -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
TopDeepLearning is a curated index of the most popular GitHub projects related to deep learning, ranked by their star count. Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly... -
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Tensorflow and deep learning
A crash course in six episodes for software developers
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,... -
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JS Bits
JavaScript concepts with code
...The repository is organized by topic so that learners can jump directly into areas they want to reinforce or explore, and community contributions are welcomed to expand coverage or add alternative explanations. Rather than being a formal textbook, js-bits acts like a developer’s code-centric cheat sheet that helps bridge the gap between abstract language specifications and real usage patterns in the browser or Node.js. -
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eslint-plugin-node
Additional ESLint's rules for Node.js
Additional ESLint's rules for Node.js. plugin:node/recommended considers both CommonJS and ES Modules. If "type":"module" field existed in package.json then it considers files as ES Modules. Otherwise it considers files as CommonJS. In addition, it considers *.mjs files as ES Modules and *.cjs files as CommonJS. plugin:node/recommended-module considers all files as ES Modules. plugin:node/recommended-script considers all files as CommonJS. -
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threadandjuc
High performance three-high-import import system
threadandjuc is a Java learning repository focused on multithreading, concurrency, and JUC concepts. It is designed to help developers understand how Java concurrent programming works through examples, explanations, and practical project-style demonstrations. The project covers topics such as threads, locks, synchronization, thread pools, concurrent collections, and high-performance data handling. It is especially useful for Java developers preparing for interviews or improving their... -
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XcodeCoverage
Code coverage for Xcode projects (Objective-C only)
XcodeCoverage is a tool that automates the generation of code coverage reports for iOS and macOS projects. It helps developers measure how much of their code is tested, facilitating better testing practices and coverage improvement. -
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Swift tips & tricks
A collection of Swift tips & tricks that I've shared on Twitter
Swift tips & tricks is a curated collection of practical Swift programming tips and tricks compiled from real-world usage and shared insights, primarily originating from short-form content like social media posts. The repository serves as a knowledge base of concise, focused techniques that demonstrate idiomatic Swift patterns, language features, and problem-solving approaches. Each tip highlights a specific concept, such as functional programming techniques, protocol specialization, error... -
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Node.JS Course
Materials, slides and other goodies from my Node.JS courses
This repository accompanies a hands-on Node.js course that builds production-minded skills through projects and exercises rather than slideware. It walks learners from fundamentals to pragmatic topics such as configuration management, process models, database integration, caching, and message queues. Security practices—input validation, secrets handling, and least-privilege IAM—are woven into examples instead of tacked on at the end. The curriculum also covers operational concerns like...
