Search Results for "code coverage" - Page 2
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Showing 61 open source projects for "code coverage"
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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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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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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Scientific Agent Skills
A set of ready to use Agent Skills for research, science, engineering
Scientific Agent Skills is an open-source collection of ready-to-use agent skills designed to turn AI coding assistants into stronger research, science, engineering, and analysis partners. It supports any AI agent compatible with the Agent Skills standard, including tools such as Cursor, Claude Code, Codex, and Gemini CLI. The repository includes 135 skills across scientific domains such as genomics, cheminformatics, clinical research, medical imaging, machine learning, physics, materials... -
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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,... -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development... -
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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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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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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PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization... -
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OSS-Fuzz Gen
LLM powered fuzzing via OSS-Fuzz
OSS-Fuzz-Gen is a companion project that helps automatically create or improve fuzz targets for open-source codebases, aiming to increase coverage in OSS-Fuzz with minimal maintainer effort. It analyses a library’s APIs, examples, and tests to propose harnesses that exercise parsers, decoders, or protocol handlers—precisely the code where fuzzing pays off. The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage signals. ... -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
...It emphasizes modularity: acoustic modeling, language modeling, tokenization, and decoding are separable pieces you can swap or ablate. The repo is aimed at pushing practical multilingual ASR—robust to accents, code-switching, and domain shifts—rather than language-by-language systems. For practitioners, it’s a starting point to study transfer, zero-shot behavior, and trade-offs between model size, compute cost, and coverage. -
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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Machine learning basics
Plain python implementations of basic machine learning algorithms
Machine learning basics repository is an educational project that provides plain Python implementations of fundamental machine learning algorithms designed to help learners understand how these methods work internally. Instead of relying on external machine learning libraries, the algorithms are implemented from scratch so that users can explore the mathematical logic and computational structure behind each technique. The repository includes notebooks that demonstrate classic algorithms such... -
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LLMs-Zero-to-Hero
From nobody to big model (LLM) hero
LLMs-Zero-to-Hero is an open-source educational project designed to guide learners through the complete process of understanding and building large language models from the ground up. The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement... -
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KG-LLM-Papers
Papers integrating knowledge graphs (KGs) and large language models
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge... -
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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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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
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minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm
minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into... -
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A Survey of Surveys
A collection of 1000+ survey papers on Natural Language Processing
A Survey of Surveys is a large curated repository that collects and organizes survey papers related to natural language processing, machine learning, and artificial intelligence research. The project aims to provide a centralized index of survey literature that summarizes major developments across different subfields of AI. Rather than focusing on code implementations, the repository functions as an academic resource that helps researchers quickly discover comprehensive survey papers... -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C is an open-source repository that provides implementations of classic algorithms and data structures written in the C programming language. The project is part of the larger “The Algorithms” initiative, which aims to create educational resources by implementing algorithms in multiple programming languages. Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine... -
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Paper-with-Code-of-Wireless-comm
Paper-with-Code-of-Wireless-communication-Based-on-DL
Paper-with-Code-of-Wireless-communication-Based-on-DL is a curated repository that collects research papers and corresponding code implementations related to the application of deep learning in wireless communication systems. The project aims to help researchers and graduate students quickly find reproducible implementations of algorithms used in modern communication research. Wireless communication research has increasingly adopted deep learning techniques to address complex tasks such as... -
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Complete Machine Learning Package
A comprehensive machine learning repository containing 30+ notebooks
Complete Machine Learning Package repository is a comprehensive educational collection of machine learning notebooks designed to teach core data science and AI concepts through practical coding examples. The project includes more than thirty notebooks that cover a wide range of topics including data analysis, statistical modeling, neural networks, and deep learning. Each notebook introduces theoretical ideas and then demonstrates how to implement them using Python libraries commonly used in... -
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onepoint
Assistant tool that integrates coding, writing, and reading functions
Onepoint is an open-source AI assistant based on Electron, designed to create the ultimate desktop productivity tool. Its initial goal was to develop a smart floating window similar to Apple's intelligent assistant that does not take up desktop space or system performance and can be quickly accessed through global hotkeys for user convenience. With ChatGPT technology, users can continuously train onepoint to generate and reconstruct content with greater accuracy (onpoint), thereby improving... -
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learn-machine-learning-in-two-months
Essential Knowledge for learning Machine Learning in two months
The learn-machine-learning-in-two-months repository is an educational open-source project designed to guide beginners through the process of learning machine learning and deep learning concepts within a structured two-month study plan. The project compiles curated resources, tutorials, and practical notebooks that introduce fundamental topics such as mathematics for machine learning, Python programming, and essential libraries like NumPy and TensorFlow. It progressively moves from... -
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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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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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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...
