Search Results for "learning" - Page 66
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Showing 4197 open source projects for "learning"
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
...These models can be loaded directly into TensorFlow pipelines and fine-tuned for new tasks using transfer learning techniques. The repository supports contributions from the community, allowing developers to submit models that become available for use by other machine learning practitioners. By enabling reusable model modules, TensorFlow Hub significantly reduces development time and computational cost when building machine learning systems. -
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Featureform
Turn your existing data infrastructure into a feature store
Featureform allows data scientists to define, manage, and serve machine learning features across your organization. The days of untitled_128.ipynb are over. Transformations, features, and training sets can be pushed from notebooks to a centralized feature repository with metadata like name, variant, lineage, and owner. Featureform's Virtual Feature Store architecture orchestrates your data infrastructure to build and maintain your training sets and production features. -
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Autodistill
Images to inference with no labeling
Autodistill uses big, slower foundation models to train small, faster supervised models. Using autodistill, you can go from unlabeled images to inference on a custom model running at the edge with no human intervention in between. You can use Autodistill on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud. -
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gopkg
Example for the go pkg's function
gopkg is a large community-driven repository of examples for Go’s standard library packages, created to fill the gap left by the relatively sparse official examples. The project organizes content so that each package has its own directory and each function within that package gets its own Markdown file with code examples. The idea is that developers can quickly look up “how do I actually use this function?” without digging through source code or scattered blog posts. The maintainer provides... -
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Neural Networks: Zero to Hero
A course on neural networks that starts all the way at the basics
Neural Networks: Zero to Hero is Andrej Karpathy’s educational course repository for learning neural networks from the ground up. It accompanies a series of video lectures where learners code and train neural networks step by step. The project starts from basic concepts and gradually builds toward more capable character-level language models. Its notebooks are written to make the mechanics visible, so learners can understand gradients, backpropagation, embeddings, multilayer perceptrons, batch normalization, and Transformer-style ideas through code. ... -
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OpenAI Quickstart Python
Python example app from the OpenAI API quickstart tutorial
openai-quickstart-python is an official OpenAI repository containing multiple Python quickstart applications that demonstrate how to use different OpenAI API endpoints, including Chat and Assistants. It provides practical, beginner-friendly examples to help developers quickly learn how to send requests, handle responses, and build basic applications using the OpenAI Python SDK. The examples folder includes small, self-contained projects showcasing common use cases like chat completions, tool... -
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ML YouTube Courses
Discover the latest machine learning / AI courses on YouTube
ML YouTube Courses is a curated index of high-quality machine learning and AI courses available on YouTube, designed to make open education easier to discover and navigate. The repository organizes lectures from top universities and educators into a structured list so learners can quickly find reputable material. It covers a wide range of topics including deep learning, NLP, probabilistic modeling, reinforcement learning, and computer vision. -
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Vanilla Web Projects
Mini projects built with HTML5, CSS & JavaScript
vanillawebprojects is a collection of small, hands-on web apps built with only HTML, CSS, and plain JavaScript to teach core front-end skills without frameworks. Each project targets a concrete concept—DOM manipulation, events, localStorage, fetch, form validation, audio/video APIs, and more—so learners see ideas applied in working code. The codebases are intentionally compact and readable, making them easy to clone, tweak, and extend. Projects progress from beginner-friendly to moderately... -
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eBook
LaTeX book with examples, open-source eBook
...This comprehensive guide covers a lot of essentials and is written in a clear and concise style, showing the result vs code. Plus, it's #opensource and freely available, creating a collaborative learning environment. In this book the I try to reveal how you can find necessary pieces of TeX code looking only at already done work. If you want to create high-quality documents with LaTeX, check out the LaTaX book on GitHub, and feel free to ask any questions you have. -
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Wikipedia2Vec
A tool for learning vector representations of words and entities
Wikipedia2Vec is an embedding learning tool that creates word and entity vector representations from Wikipedia, enabling NLP models to leverage structured and contextual knowledge. -
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OnnxStream
Lightweight inference library for ONNX files, written in C++
The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which at the cost of RAM usage. So I decided to write a super small and hackable inference library specifically focused on minimizing memory consumption: OnnxStream. OnnxStream is based on the idea of decoupling the inference engine from the component responsible for providing the model weights, which is a class derived from WeightsProvider. ... -
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BA_PY
BA_PY: Optimize Your Workflow with Python!
mbapy is a Python package that includes a collection of useful Python scripts as sub-modules, and it's goal is Basic for All in Python. mbapy primarily focus on data works, including data-retrieval, data-management, data-visualization, data-analysis and data-computation. It is built for both python-users and command-line-users. -
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Computer vision projects
computer vision projects | Fun AI projects related to computer vision
...Many of the projects illustrate how computer vision algorithms can interact with hardware platforms, including robotics systems and edge computing devices. The repository provides examples that combine machine learning models with real-world applications such as robotic arms, video analysis, and automated visual measurement systems. -
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Django LMS
A learning management system using django web framework
django-lms is an open-source Learning Management System (LMS) built with Django and designed for ease of use and extensibility. It allows administrators to manage courses, lessons, quizzes, and users in an educational environment. The project includes a clean UI and backend tools to help educators create and track learning content. -
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dinrhiw2-180824-sync
Dinrhiw2 is open source machine learning library.
Dinrhiw2 is open source machine learning library. -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already ship with Sonnet, making it quite powerful and yet simple at the same time. ... -
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Geographical Adventures
Geography game about delivering packages
...It includes implementations of terrain generation, map systems, and spatial algorithms that simulate real-world geographical features. The project is designed as both a learning resource and a demonstration of procedural techniques, allowing users to explore how landscapes and environments can be generated algorithmically. It emphasizes modular design, enabling different components such as terrain, noise functions, and rendering systems to be reused or extended. The code is structured to be approachable, making it suitable for developers interested in game development or simulation. ... -
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Nginx Tutorial
This is a minimalist tutorial on Nginx designed to help beginners
Nginx Tutorial is a Chinese-language learning repository designed to help beginners understand and use Nginx quickly. It explains the server’s role as a web server, reverse proxy, load balancer, and mail proxy. The introductory material covers essential commands, configuration files, logging, worker processes, and connection settings. Practical guides demonstrate HTTP and HTTPS reverse proxies, load balancing, static website hosting, file servers, and cross-origin request handling. ... -
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Weak-to-Strong
Implements weak-to-strong learning for training stronger ML models
Weak-to-Strong is an OpenAI research codebase that implements the concept of weak-to-strong generalization, as described in the accompanying paper. The project provides tools for training larger “strong” models using labels or guidance generated by smaller “weak” models. Its core functionality focuses on binary classification tasks, with support for fine-tuning pretrained language models and experimenting with different loss functions, including confidence-based auxiliary losses. The... -
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AI-Aimbot
CS2, Valorant, Fortnite, APEX, every game
AI-Aimbot is a computer vision project that demonstrates how artificial intelligence can be used to automatically identify and target opponents in video games. The system uses an object detection model based on the YOLOv5 architecture to detect human-shaped characters in gameplay screenshots or video frames. Once a target is identified, the program automatically adjusts the player’s aim toward the detected target, effectively automating the aiming process in first-person shooter games. The... -
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Quil
Main repo, Quil source code
Quil blends Clojure's expressive functional programming with Processing’s creative graphics and animation capabilities, offering a DSL for drawing and interactive visuals in a dynamic, artistic way. In one hand Quil holds Processing, a carefully crafted API for making drawing and animation extremely easy to get your biscuit-loving chops around. In the other she clutches Clojure, an interlocking suite of exquisite language abstractions forged by an army of hammocks and delicately wrapped in... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. -
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PromptTools
Open-source tools for prompt testing and experimentation
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground. -
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Exposure Correction
Learning multi-scale deep model correcting over- and under- exposed
Exposure_Correction is a research project that provides the implementation for the paper Learning Multi-Scale Photo Exposure Correction (CVPR 2021). The repository focuses on correcting poorly exposed photographs, handling both underexposure and overexposure using a deep learning approach. The method employs a multi-scale framework that learns to enhance images by adjusting exposure levels across different spatial resolutions. -
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SSD in PyTorch 1.0
High quality, fast, modular reference implementation of SSD in PyTorch
This repository implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch, pytorch-ssd and maskrcnn-benchmark. This repository aims to be the code base for research based on SSD. Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can...