Search Results for "learning" - Page 21
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Showing 1132 open source projects for "learning"
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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MVVM
Analyze the principle of vue implementation and implement mvvm
...Because it mirrors ideas found in larger frameworks, it’s an excellent teaching aid for developers who want to understand why features like computed properties and watchers behave as they do. It is not intended as a production framework; instead, it’s a compact lab for learning the principles behind MVVM and modern reactive libraries. -
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codi.vim
The interactive scratchpad for hackers
...It focuses on minimal setup so you can open a buffer, set a filetype, and start experimenting immediately. Because results update incrementally, it is useful for learning, debugging, or documenting small examples. It turns Vim into a lightweight computational notebook while keeping the modal editing experience intact. -
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git-chglog
CHANGELOG generator implemented in Go (Golang)
Package chglog implements the main logic for the CHANGELOG generate. git-chglog internally uses the git command to get data to include in the CHANGELOG. The basic steps are as follows. Get all the tags. Get the commits contained between tagA and tagB. Execute all tags corresponding to the tag query that was specified in Steps 1 and 2. The compiled docker images are maintained on quay.io. git-chglog requires configuration files and templates to generate a CHANGELOG. However, it is a waste of... -
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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Proteus Model Builder
GUI for training of neural network models for GuitarML Proteus
...GuitarML's work on Proteus, NeuralPi and Proteusboard (hardware) is amazing. https://github.com/GuitarML Yet, it is not easy to wrap your head around if you are not familiar with programming, AI, machine learning, neuronal networks. So, Keith Bloemer a.k.a. GuitarML set up a Google Colab script to give people the Opportunity to train their own models online. Still, I thought that things could be easier, and I wanted a faster way to work with the python scripts. So I automated some things on my Windows 10 machine. I assume, that most musicians use this OS. ... -
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UnionML
Build and deploy machine learning microservices
...Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. ... -
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KubeOperator
An open source, lightweight Kubernetes distribution
...Support online environment and offline environment deployment. Provides a visual web UI. Supports cluster planning, deployment and operations. Easily run workloads like machine learning, high-performance computing, and more. Quickly deploy and manage applications in K8S. Only two steps to complete the KubeOperator installation and deployment. -
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Ruby 2D
The Ruby 2D gem
...Built atop SDL2 and OpenGL, Ruby2D abstracts away the complexity of low-level graphics programming while exposing enough control for performance and flexibility. It supports images, text, sounds, and basic geometric shapes, making it ideal for learning graphics or quickly prototyping ideas with Ruby. The library is cross-platform and lightweight, staying true to Ruby’s principle of developer happiness. -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
...It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is great for customization and teaching purposes. -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. ... -
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Bert Client
Simple and Easy-to-Use REST API client for server developers.
...Bert Client is perfect for developers who want a lightweight and easy-to-use tool for testing their APIs. With Bert Client, you can quickly test your API endpoints without having to worry about setting up complex configurations or dealing with a steep learning curve. Bert Client supports sending requests with an Authorization token, making it easy to test APIs that require authentication. The response from the API is displayed in a user-friendly format, making it easy to see the results of your API calls. -
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Resources for Competitive Programming
Competitive Programming & System Design Resources
...It gathers video tutorials, practice platforms, algorithm references, interview preparation links, and system design materials in one place. The repository is not a software library but a structured learning hub for people who want to improve algorithmic thinking and technical interview readiness. It points users toward platforms such as Codeforces, CodeChef, LeetCode, AtCoder, TopCoder, SPOJ, HackerRank, and Project Euler. It also lists books, roadmaps, blogs, and mock interview resources for deeper study. The project is useful for beginners who need direction and for experienced learners who want a consolidated reference list. -
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quantitative
Quantized transactions python3
The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew substantial attention, suggesting the material is meant to be both educational and hands-on. ... -
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go-coffeeshop
A practical event-driven microservices demo
...The project is structured to separate concerns clearly, with layers for domain logic, application services, infrastructure, and interfaces. It showcases best practices for building microservices, including dependency injection, testing strategies, and modular design. The repository is intended as a learning resource for developers who want to understand how to apply architectural patterns in Go projects. It also includes examples of integrating external systems and handling real-world scenarios such as order processing and inventory management. -
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Data science blogs
A curated list of data science blogs
Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. The repository includes links to personal blogs, professional publications, and educational resources, often accompanied by RSS feeds for easy subscription and content tracking. ... -
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Beautiful Responsive Website Templates
Templates For Learning & Implementation - Quickly Create Your Websites
Categories : Website Design, Website Development, Website Creation, Website Templates, Responsive Website, Beautiful Website -
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NeuMan
Neural Human Radiance Field from a Single Video (ECCV 2022)
...It supports novel view and novel pose synthesis, enabling compositional results like transferring reconstructed humans into new scenes. The pipeline separates human/body and environment, learning consistent geometry and appearance to support animation. Demos showcase sequences such as dance and handshake, and the code provides guidance for running evaluations and rendering. As a research release, it serves both as a baseline and as a starting point for work on human-centric NeRFs. The emphasis is on practical reconstruction quality from minimal capture setups. ... -
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Git Tips
Compact knowledge base of Git command tips and workflows
...Because entries are concise and independent, you can dip in at any point and learn something useful in a minute or two. It serves both as a cheat sheet for experienced developers and a learning aid for those new to version control. -
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Twinify
Privacy-preserving generation of a synthetic twin to a data set
twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI).... -
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Scotty
Haskell web framework inspired by Ruby's Sinatra, using WAI and Warp
...Scotty is built on top of the WAI (Web Application Interface) and Warp server, making it fast and scalable. It emphasizes simplicity and ease of use, making it ideal for small- to medium-sized services or for developers learning web programming in Haskell. -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair... -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. ... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. ... -
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Rakkas
Bleeding-edge React framework powered by Vite
...If you need a stable React framework try Next.js, Remix, or Gatsby. create-rakkas-app project initializer comes with many features, all of which are optional but we strongly recommend enabling TypeScript and the generation of a demo project on your first try because self-documenting type definitions allow for a smoother learning curve and the demo project source code comes with plenty of comments. -
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. ...