Search Results for "code coverage" - Page 2
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163 projects for "code coverage" with 1 filter applied:
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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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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
Companion notebooks for Deep Learning is a collection of Jupyter notebooks that accompany François Chollet’s deep learning curriculum, providing hands-on implementations of key concepts using practical examples. The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. The... -
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CVPR 2026
Collection of CVPR 2026 Papers and Open Source Projects
CVPR2026-Papers-with-Code is a community-maintained repository that collects research papers and corresponding open-source implementations from the CVPR 2026 conference and related computer vision research. The repository acts as a continuously updated catalog of cutting-edge research across a wide range of topics including computer vision, multimodal AI, generative models, diffusion systems, autonomous driving, medical imaging, and remote sensing. Each entry typically links to the research... -
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Machine Learning Tutorials Repository
Dive deep into the realms of Machine Learning and other topics
The Machine Learning Tutorials Repository is a comprehensive collection of resources, examples, and implementations designed to help users understand and apply machine learning concepts. It covers a wide range of topics, including supervised learning, unsupervised learning, neural networks, and data preprocessing techniques. The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. It includes... -
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dive-into-llms
"Dive into LLMs" series of practical programming tutorials
The dive-into-llms project is an educational resource designed to provide a comprehensive introduction to large language models and their underlying concepts. It combines theoretical explanations with practical examples, guiding users through topics such as model architecture, training processes, and inference techniques. The repository is structured as a learning pathway, making it accessible to both beginners and intermediate practitioners interested in understanding how LLMs work. It... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
The Data-science repository from CodeCutTech is a curated collection of educational content focused on practical tools and workflows used in modern data science projects. Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by... -
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tapjs
Test Anything Protocol tools for node
...An easily extensible TAP test framework, with outstanding TypeScript support, a CLI, plenty of assertion methods, snapshots, object/method spies, module mocking, file system fixtures, lifecycle hooks, test filtering, comprehensive code coverage analysis, color-accessible test reporters, and more. Software testing is a software and user experience design challenge that balances on the intersection of many conflicting demands. -
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Caffeine for Laravel
Keeping Your Laravel Forms Awake.
Prevent forms from timing out when submitting them after leaving them on-screen for a considerable amount of time. (Laravel defaults to 120 minutes, but that is configurable and could be different site-by-site.) To achieve this, we are sending a caffeine-drip (a request at regular intervals) to keep the session from timing out. This is only implemented on pages with a _token field, so all other pages will time-out as normal. -
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PHP Docs Samples
A collection of samples on how to call Google Cloud services
PHP Docs Samples repository is a broad collection of PHP examples that demonstrate how to call and work with Google Cloud services from PHP applications. It is designed as a companion to Google Cloud documentation, giving developers ready-to-run code patterns they can study, adapt, and integrate into their own projects. Rather than focusing on a single product, the repository spans many services and use cases, making it useful for developers who need a central reference point for PHP-based... -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. The repository... -
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Transfer Learning Repo
Transfer learning / domain adaptation / domain generalization
Transfer Learning Repo is an open-source repository that compiles resources, code implementations, and academic references related to transfer learning and its related research areas. The project functions as a large knowledge hub that organizes papers, tutorials, datasets, and software implementations across topics such as domain adaptation, domain generalization, multi-task learning, and few-shot learning. The repository includes surveys and theoretical explanations that help readers... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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QuantumOptics.jl
Library for the numerical simulation of closed as well as open quantum
...The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics, not on the numerics. Every function in the framework has been severely tested with all tests and their code coverage presented on the framework's GitHub page. -
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DevOps Roadmap 2026
DevOps Roadmap for 2026. with learning resources
DevOps Roadmap is a structured 2026 learning guide for people preparing for DevOps engineering roles. It presents the field as a sequence of practical competencies rather than a list of fashionable products. The path begins with Git, a programming language, Linux, scripting, networking, security, and server administration. It then advances through containers, Kubernetes, infrastructure as code, CI/CD, monitoring, observability, cloud platforms, and software engineering practices. A bonus... -
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JavaGuide
"Java Learning + Interview Guide" covers the core Java knowledge
JavaGuide is an open source knowledge base and learning resource for Java developers, created and maintained by Snailclimb. The project organizes and explains a wide range of Java-related concepts, from language fundamentals to advanced topics such as concurrency, JVM internals, distributed systems, and high availability design. It is especially popular among developers preparing for technical interviews, as it compiles common knowledge points, detailed explanations, and source code analyses... -
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Modern JavaScript Cheatsheet
Cheatsheet for the JavaScript knowledge
Modern JavaScript Cheatsheet is a reference guide for developers who know basic JavaScript but find contemporary codebases difficult to read. It focuses mainly on language patterns introduced with ES2015 and commonly encountered in frameworks such as React. Each topic combines concise explanations, examples, and links for deeper study. Covered concepts include let and const, arrow functions, default parameters, destructuring, array methods, spread syntax, and property shorthand. It also... -
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React in patterns
A free book that talks about design patterns/techniques
React in patterns is a free book about common design patterns and techniques used in React development. It is written for developers who already understand React basics and want to think more clearly about application structure. The book explains concepts such as communication, event handlers, composition, controlled inputs, container components, one-way data flow, Flux, Redux, dependency injection, styling, and third-party integration. It includes source code examples that support the... -
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LLM Agents Papers
Must-read Papers on LLM Agents
LLM Agent Papers is an open-source repository that curates research papers related to large language model agents and autonomous AI systems. The project organizes academic literature that explores how language models can act as agents capable of reasoning, planning, and interacting with external tools or environments. Rather than providing software code, the repository functions as a structured knowledge base that helps researchers navigate the rapidly expanding field of agent-based AI... -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer... -
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Python Core 50 Courses
Structured learning path that organizes Python fundamentals
Python-Core-50-Courses is a structured learning path that organizes Python fundamentals into 50 digestible lessons designed for steady, incremental progress. The curriculum starts with the basics—syntax, variables, data types, and control flow—then advances to functions, modules, object-oriented programming, and common standard-library utilities. Each lesson favors hands-on examples and short exercises so learners can immediately apply new concepts in code. Later sections typically touch on... -
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Hacking with Swift
The project source code for Hacking with iOS
HackingWithSwift is an extensive open-source repository that accompanies a popular tutorial series focused on teaching Swift programming for iOS development. It contains a large collection of example projects, exercises, and complete applications that guide learners from beginner to advanced levels. The repository is structured into different learning tracks, including UIKit-based development and modern SwiftUI approaches, allowing developers to explore multiple paradigms within the Apple... -
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Python Programming Hub
Learn Python and Machine Learning from scratch
Python Programming Hub repository by Tanu-N-Prabhu is an educational resource designed to help programmers learn Python programming and data science concepts through practical examples and notebooks. The project contains a wide range of tutorials and exercises that cover Python fundamentals, programming concepts, and applied techniques for data analysis and machine learning. Many sections are implemented as Jupyter notebooks, allowing learners to run code interactively while reading... -
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whenwords
A relative time formatting library, with no code
whenwords is a concise, open-source natural language scheduler that helps applications interpret date/time expressions (“tomorrow”, “next Friday at 3”, “in two hours”) in ordinary human language and convert them into precise scheduled events. It combines robust parsing logic with a flexible API so developers can embed scheduling understanding into chatbots, task managers, calendar tools, or productivity apps without building complex date interpreters from scratch. The library handles a wide... -
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Beginner JavaScript
Slam Dunk JavaScript
Beginner JavaScript is the companion repository to a hands-on course that teaches modern JavaScript from the ground up using practical exercises and real code. It focuses on fundamentals—variables, types, functions, arrays, objects, DOM manipulation, and events—while introducing ES6+ features in approachable steps. The materials encourage learning by doing, with interactive challenges, starter files, and solutions you can compare against your own attempts. Clear explanations and incremental... -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
n8n-mcp is a Model Context Protocol (MCP) server that turns the n8n workflow platform into a set of first-class, typed tools an AI assistant can understand and operate. It exposes structured knowledge of n8n nodes and operations so an agent can reason about workflows, parameters, and executions without scraping docs or guessing API shapes. The server focuses on making Claude Desktop (and other MCP-capable clients) “n8n-literate,” enabling tasks such as inspecting existing workflows,... -
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Made With ML
Learn how to develop, deploy and iterate on production-grade ML
Made-With-ML is an open-source educational repository and course designed to teach developers how to build production-grade machine learning systems using modern MLOps practices. The project focuses on bridging the gap between experimental machine learning notebooks and real-world software systems that can be deployed, monitored, and maintained at scale. It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets,...
