Search Results for "learn" - Page 13
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Showing 1944 open source projects for "learn"
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99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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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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Cleanlab
The standard data-centric AI package for data quality and ML
...This package helps you find label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box. -
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compromise
Modest natural-language processing
Language is complicated and there's a gazillion words. Compromise is a javascript library that interprets and pre-parses text and makes some reasonable decisions so things are way easier. Compromise tries its best to parse text. it is small, quick, and often good-enough. It is not as smart as you'd think. Conjugate and negate verbs in any tense. Play between plural, singular and possessive forms. Interpret plain-text numbers. Handle implicit terms. Use it on the client-side or as an... -
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Alook
The collaboration layer for your AI workforce
...It is designed for developers, solo founders, and teams that want multiple AI agents to handle development, operations, research, and routine work with clearer structure. Alook also emphasizes memory and traceability, so agents can remember past decisions, learn preferences, and keep a record of instructions and replies. Its main value is turning separate AI coding tools into an organized, always-on operating system for agent-based work. -
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Zingg
Scalable master data management and identity resolution
Zingg is an open-source entity resolution and master data management platform for finding duplicate, related, or matching records across large datasets. It uses machine learning to learn how records should be compared, reducing the need for brittle hand-written matching rules. The project is designed for data engineering and analytics teams working on customer 360, supplier 360, deduplication, fuzzy matching, data quality, and golden record workflows. Zingg runs on Apache Spark and can scale to large data lake, warehouse, and cloud platform environments. ... -
$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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AI Engineering from Scratch
Learn it. Build it. Ship it for others
AI Engineering from Scratch is a comprehensive open-source curriculum designed to teach artificial intelligence by building every component from first principles rather than relying on prebuilt frameworks. The project is structured into more than 20 phases and hundreds of lessons, covering topics that range from foundational mathematics to advanced systems such as large language models, retrieval pipelines, and multi-agent architectures. Each lesson emphasizes hands-on implementation,... -
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anti-distill
Anti-distillation for employee Skills
anti-distill is a research-oriented project focused on protecting machine learning models from knowledge distillation attacks, where smaller models attempt to replicate the behavior of larger proprietary systems. The project explores techniques that make it harder for external models to learn from outputs, thereby preserving intellectual property and model uniqueness. It likely introduces methods such as output perturbation, watermarking, or response shaping to prevent accurate imitation. The system is particularly relevant in contexts where models are exposed via APIs and risk being reverse-engineered through repeated querying. ... -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
...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 material is designed to be accessible while still covering advanced topics, making it suitable for both beginners and intermediate practitioners. It leverages modern libraries and frameworks to demonstrate real-world applications of deep learning techniques. The notebooks also emphasize best practices in model training, evaluation, and deployment. ... -
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics such as computer vision, agent systems, federated learning, distributed systems, adversarial attacks, and generative AI. ... -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
...The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation. -
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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learning
A log of things I'm learning
...The content is organized into categories that cover both core engineering skills and adjacent technologies, enabling readers to follow a practical roadmap for developing strong technical foundations. The repository emphasizes clear explanations, curated resources, and concise notes designed to help developers learn complex topics efficiently. Because it is updated regularly, it reflects evolving trends in software engineering and emerging technologies such as modern AI systems. -
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. By solving progressively... -
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Super comprehensive deep learning notes
Super Comprehensive Deep Learning Notes
Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. ... -
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Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
...Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator. -
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LatentMAS
Latent Collaboration in Multi-Agent Systems
LatentMAS is an advanced framework for multi-agent reinforcement learning (MARL) that uses latent variable modeling to bridge perception and decision-making in environments where agents must coordinate under uncertainty. It provides mechanisms for agents to learn high-level latent representations of states, which simplifies complex sensory inputs into compact, actionable embeddings that facilitate both individual policy learning and inter-agent coordination. Using this latent space, the framework enables Multi-Agent Systems (MAS) to scale more effectively in environments with high dimensionality — such as robotics, simulated physics tasks, and strategic games — by reducing redundant learning burdens and focusing agent exploration. ... -
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Agentic Data Scientist
An end-to-end Data Scientist
...Each agent is designed to independently call functions, interact with data sources, and adapt to uncertainties during processing, enabling iterative refinement of models without manual coordination. The framework supports interoperability with existing data tools and libraries, letting the agents leverage libraries like pandas, scikit-learn, and visualization frameworks to perform real computations rather than mock demonstrations. -
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Motor
The async Python driver for MongoDB and Tornado or asyncio
...Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. Because it integrates with popular async ecosystems like FastAPI, Sanic, and aiohttp, Motor is a natural fit for modern async Python stacks where throughput and responsiveness matter. It also supports change streams, grid file system (GridFS), and the full range of CRUD and aggregation operations available in MongoDB. -
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ComfyUI Examples
Examples of ComfyUI workflows
ComfyUI_examples is the companion repository for ComfyUI that collects ready-made example workflows, nodes, and compositions to help users learn the node-based interface for AI image generation. Instead of starting from an empty graph, you can open an example and see how prompts, samplers, models, and image processing steps are wired together. This makes ComfyUI more approachable for people coming from “one text box” generators, because they can reverse-engineer complex pipelines visually. ... -
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Memories
Build a full stack MERN application
Project MERN Memories is a full-stack application built as a learning tutorial, using the MERN stack: React on the front end, Node.js and Express on the back end, and MongoDB for data persistence. The app is called “Memories” and allows users to post interesting events from their lives (memories), providing a simple social media–style interface and back-end API to support create, read, update, delete of posts. The repository is tied to a video tutorial series that covers the project from... -
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TIL
Today I Learned
...Topics span everyday developer concerns: shell one-liners, Git incantations, editor tricks, language quirks, and small debugging patterns that save time. Because each note is atomic, the collection grows organically without becoming a tangled tutorial or book; readers can dip in anywhere and learn something useful in a minute. The repo format also encourages community contributions and personal forking, making it a template for teams to build their own shared knowledge base. Over years, it becomes both a reference and a record of the author’s learning journey, with the git history revealing how practices evolved. -
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vimrc
The ultimate Vim configuration (vimrc)
...It also includes update scripts and guidance for keeping plugins current, which lowers the maintenance burden for users who just want Vim to work well. Documentation explains the layout and keybindings so you can learn quickly, then customize as you grow more comfortable. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
...The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. It emphasizes ethical considerations and model evaluation—accuracy is not the only metric—so students learn to validate and communicate results responsibly. By the end, participants can build end-to-end ML experiments, interpret outputs, and iterate with confidence rather than just copying code. -
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CSS Inspiration
Curated collection of interesting, creative, or inspiring CSS effects
...Many examples lean on contemporary features—custom properties, filters, blend modes, gradients, and keyframes—serving as both inspiration and a practical cookbook. Because each demo focuses on a single idea, it’s an effective way to learn new techniques without wading through a full framework. The project thrives on experimentation and community interest, making it a frequent reference for designers, front-end engineers, and educators who want visually striking yet lightweight solutions. -
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Taipy
Turns Data and AI algorithms into production-ready web applications
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape.... -
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UMAP
Uniform Manifold Approximation and Projection
Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction. It is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional... -
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Saloon
Build beautiful API integrations and SDKs with Saloon
Saloon is a PHP library that gives you the tools to build beautifully simple API integrations and SDKs. Saloon moves your API requests into reusable classes so you can keep all your API configurations in one place. Saloon comes with many exciting features out of the box like recording requests in your tests, caching, OAuth2, and pagination. It's a great starting point for building simple, standardized API integrations in your application. Packed full of features like request recording,...