Ml Engineering Github Topics Github

TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation. The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more! An AI-powered data science team of agents to help you perform common data science tasks 10X faster. Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng Ultimate AI research and engineering course

Explore these top machine learning repositories to build your skills, portfolio, and creativity through hands-on projects, real-world challenges, and AI resources. Machine learning is a vast and dynamic field that encompasses a wide range of domains, including computer vision, natural language processing, core machine learning algorithms, reinforcement learning, and more. While taking courses can help you learn the theoretical foundations, they often don't provide the hands-on experience needed to solve real-world problems or demonstrate your abilities to potential employers. To become job-ready as a machine learning engineer, it's essential to build a diverse portfolio of projects that showcase both your technical skills and your practical experience. In this article, we will review 10 GitHub repositories that feature collections of machine learning projects. Each repository includes example codes, tutorials, and guides to help you learn by doing and expand your portfolio with impactful, real-world projects.

Link: ChristosChristofidis/awesome-deep-learning Updated on Sep 10, 2025 | 26 min read | 24.06K+ views Curious about using GitHub Copilot in your terminal? Here’s our guide to GitHub Copilot CLI, including a starter kit with the best prompts for a wide range of use cases. How GitHub Copilot works today—including mission control—and how to get the most out of it. Here’s what you need to know.

Take a look inside our automated pipeline for rapid, rigorous evaluation for the GitHub MCP Server. Learn how to bring structure and security to your AI ecosystem with the GitHub MCP Registry, the single source of truth for managing and governing MCP servers. Find out about the latest custom models powering the completions experience in GitHub Copilot. 10 GitHub Repositories to Boost Your Machine Learning Skills (With Real Projects & Code) It’s easy to watch machine learning tutorials and feel like you're learning. But when it’s time to build something real — the struggle begins.

That’s because true mastery doesn’t come from passive learning. It comes from building, breaking, and repeating. GitHub offers the perfect playground: real code, working projects, datasets, and best practices in action. Whether you're just starting or sharpening your ML chops, these 10 repositories will guide you into real-world implementation. A treasure chest of diverse ML projects — from basic classification problems to advanced deep learning models. In the age of data-driven decision-making, machine learning (ML) has become a cornerstone for businesses across industries.

However, deploying ML models and maintaining them in production requires more than just coding skills; it demands a solid understanding of MLOps (Machine Learning Operations). To help you navigate this crucial field, we've curated a list of 10 GitHub repositories that offer valuable resources, tools, and frameworks to help you master MLOps. In this article, we will explore, 10 GitHub Repositories to Master MLOps. These 10 GitHub repositories offer a diverse range of tools to help you build, scale, and monitor machine-learning models in production environments. Description: This repository hosts a collection of Jupyter notebooks that showcase the various capabilities of Azure Machine Learning. You'll find practical examples of model training, deployment, and MLOps workflows, making it a great starting point for those interested in Azure's ecosystem.

Link: https://github.com/Azure/MachineLearningNotebooks Description: This repository provides a practical implementation of MLOps using Python and Azure. It covers the entire ML lifecycle—from data preparation to deployment and monitoring—making it an excellent resource for hands-on learning. Machine Learning (ML) is transforming industries, from healthcare to finance, and the best way to learn ML is through real-world projects. With thousands of repositories available, GitHub is a treasure trove for learners and professionals alike. But which projects truly help you grow your skills?

In this guide, we explore the 7 Best GitHub Machine Learning Projects to Boost Your Skills. These projects are hand-picked based on their educational value, community support, documentation quality, and real-world applicability. Whether you’re a beginner or an experienced data scientist, these repositories will elevate your understanding and hands-on capabilities. Scikit-learn is the most beginner-friendly with strong documentation and a gentle learning curve. Most are licensed under permissive licenses (e.g., MIT, Apache 2.0), but always check each repository’s license. Start by reading the CONTRIBUTING.md file in the repo, open issues, and submit pull requests following community guidelines.

The blog covers machine learning courses, bootcamps, books, tools, interview questions, cheat sheets, MLOps platforms, and more to master ML and secure your dream job. Mastering machine learning (ML) may seem overwhelming, but with the right resources, it can be much more manageable. GitHub, the widely used code hosting platform, is home to numerous valuable repositories that can benefit learners and practitioners at all levels. In this article, we review 10 essential GitHub repositories that provide a range of resources, from beginner-friendly tutorials to advanced machine learning tools. This comprehensive 12-week program offers 26 lessons and 52 quizzes, making it an ideal starting point for newcomers. It serves as a starting point for those with no prior experience with machine learning and looks to build core competencies using Scikit-learn and Python.

Each lesson features supplemental materials including pre- and post-quizzes, written instructions, solutions, assignments, and other resources to complement the hands-on activities. This GitHub repository serves as a curated index of quality machine learning courses hosted on YouTube. By collecting links to various ML tutorials, lectures, and educational series into one centralized location from providers like Clatech, Stanford, and MIT, the repo makes it easier for interested learners to find video-based ML... Docling - Transform any document into LLM ready data Transform any document into LLM-ready data! Docling is an open-source toolkit that parses unstructured files into clean, structured formats Markdown, JSON, and more.

Parses PDFs, DOCX, HTML, PPTX, XLSX, images, and audio Handles complex layouts: tables, code, formulas, and multi-column flows Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular. 😎 A curated list of awesome MLOps tools 🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng Frouros: an open-source Python library for drift detection in machine learning systems.

People Also Search

• ml-engineering · GitHub Topics · GitHub
• 10 GitHub Repositories for Machine Learning Projects
• 25+ Machine Learning Projects on GitHub with Source Code 2025 - upGrad
• The latest on AI & ML - The GitHub Blog
• 10 GitHub Repositories to Boost Your Machine Learning Skills ... - Medium
• 10 GitHub Repositories to Master MLOps - GeeksforGeeks
• 7 Best GitHub Machine Learning Projects to Boost Your Skills
• 10 GitHub Repositories to Master Machine Learning - KDnuggets
• 5 GitHub Repositories for AI Engineers
• machine-learning-engineering · GitHub Topics · GitHub