Search Results for "learning" - Page 90
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Showing 4736 open source projects for "learning"
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React For Beginners
Starter files for learning React.js with React for Beginners
...It emphasises component architecture, state management, data flows, routing, and deployment rather than just “hello world”. For those new to React it lowers friction by giving much of the boilerplate already set up, allowing focus on learning. -
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Machine Learning & Deep Learning
machine learning and deep learning tutorials, articles
Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. -
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text_renderer
Generate text images for training deep learning ocr model
Text Renderer is a Python utility for generating synthetic text images used to train optical character recognition models. It supports Latin and non-Latin writing systems and produces matching labels alongside the generated images. Users can supply their own corpora, fonts, character sets, backgrounds, and YAML configuration files. Available effects include perspective distortion, random cropping, curved text, borders, variable spacing, lines, embossing, color changes, inversion, and blur. A... -
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AI Platform Training and Prediction
Cloud ML Engine repo
AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions. The repository covers the full machine learning lifecycle, including data preprocessing, model training, hyperparameter tuning, evaluation, and prediction serving. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Zenoss Community Edition
Zenoss - Intelligent IT Operations Management
Zenoss provides software-defined IT operations for the world’s largest organizations. We deliver the ultimate level of IT service health with simplicity by providing the most granular and intelligent IT service modeling possible, at any scale, and sharing these unique insights with other IT operations management (ITOM) tools to make them more efficient. Zenoss Community Edition is not a “demo” or trial version of Zenoss Enterprise or Zenoss Cloud! Before You install Zenoss Community... -
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NGSpop
NGSpop: identifying & visualizing sequence variation in deepvariant
*NOTICE* The official software(NGSpop) will be updated soon, so please visit us in 2/29. Thank you. -
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pranaOS
Smart Operating System for x86, ARM, Mobile, Watch
...It is designed for the x86_64 architecture and features a custom shell, task scheduler, and keyboard driver. With a strong focus on education, pranaOS serves as a base for experimenting with kernel development and learning how different subsystems interact in a functioning OS. -
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MoCo v3
PyTorch implementation of MoCo v3
MoCo v3 is a PyTorch reimplementation of Momentum Contrast v3 (MoCo v3), Facebook Research’s state-of-the-art self-supervised learning framework for visual representation learning using ResNet and Vision Transformer (ViT) backbones. Originally developed in TensorFlow for TPUs, this version faithfully reproduces the paper’s results on GPUs while offering an accessible and scalable PyTorch interface. MoCo v3 introduces improvements for training self-supervised ViTs by combining contrastive learning with transformer-based architectures, achieving strong linear and end-to-end fine-tuning performance on ImageNet benchmarks. ... -
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Awesome Explainable Graph Reasoning
A collection of research papers and software related to explainability
A collection of research papers and software related to explainability in graph machine learning. Deep learning methods are achieving ever-increasing performance on many artificial intelligence tasks. A major limitation of deep models is that they are not amenable to interpretability. This limitation can be circumvented by developing post hoc techniques to explain the predictions, giving rise to the area of explainability. -
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igel
Machine learning tool that allows you to train and test models
A delightful machine learning tool that allows you to train/fit, test, and use models without writing code. The goal of the project is to provide machine learning for everyone, both technical and non-technical users. I sometimes needed a tool sometimes, which I could use to fast create a machine learning prototype. Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML. -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results. ... -
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Music Source Separation
Separate audio recordings into individual sources
...The repository provides training scripts (e.g. using datasets such as MUSDB18), preprocessing steps (audio-to-HDF5 packing, indexing), evaluation pipelines, and inference scripts to perform separation on arbitrary audio files. This makes the project useful both for researchers in music information retrieval / audio machine learning and for hobbyists or practitioners who want to experiment with remixing, karaoke, or audio editing. -
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Awesome Decision Tree Papers
A collection of research papers on decision, classification, etc.
A collection of research papers on decision, classification and regression trees with implementations. -
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codeforces-go
Solutions to Codeforces by Go
Golang algorithm competition template library. Due to the complexity of algorithm knowledge points, it is necessary to classify the algorithms you have learned and the questions you have done. An algorithm template should cover the following points. Basic introduction to the algorithm (core idea, complexity, etc.) Reference links or book chapters (good material) Template code (can contain some comments, usage instructions) Template supplements (extra codes in common question types, modeling... -
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LenMus
LenMus is a free program for learning music theory.
*** Development moved to GitHub at https://github.com/lenmus/lenmus *** LenMus is a free program for learning music. It allows you to focus on specific skills and exercises, on both theory and aural training. The different activities can be customized to meet your needs. It includes an score editor. -
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vue2-happyfri
Learning-oriented app that recreates a mobile food-ordering experience
vue2-happyfri is a learning-oriented Vue 2 application that recreates a mobile food-ordering experience to demonstrate how to structure a real-world single-page app. It shows how to compose UI from reusable components, wire up routing between views, and manage shared state for carts, users, and menus. The project emphasizes responsive, touch-friendly interactions and small polish details—like transitions, toasts, and loading states—that make the app feel production-ready. -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. ... -
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MuJoCo-py
mujoco-py allows using MuJoCo from Python 3
mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated. It provides utilities for loading models, running simulations, and accessing simulation states in real time, along with visualization tools for rendering environments. ... -
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ReinforcementLearningAnIntroduction.jl
Julia code for the book Reinforcement Learning An Introduction
This project provides the Julia code to generate figures in the book Reinforcement Learning: An Introduction(2nd). One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl. -
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Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
DeepLearning-500-questions is a comprehensive handbook that compiles 500 important questions on deep learning, curated to serve as a valuable reference for AI engineer interviews and self-study. Edited by Tan Jiyong with contributions from Guo Zizhao, Li Jian, and Dian Songyi, the book systematically covers both theoretical foundations and practical applications of deep learning. The first sections focus on essential mathematics, machine learning basics, and deep learning foundations, establishing the groundwork for more advanced topics. ... -
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Record matching software
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VQGAN-CLIP web app
Local image generation using VQGAN-CLIP or CLIP guided diffusion
VQGAN-CLIP has been in vogue for generating art using deep learning. Searching the r/deepdream subreddit for VQGAN-CLIP yields quite a number of results. Basically, VQGAN can generate pretty high-fidelity images, while CLIP can produce relevant captions for images. Combined, VQGAN-CLIP can take prompts from human input, and iterate to generate images that fit the prompts. Thanks to the generosity of creators sharing notebooks on Google Colab, the VQGAN-CLIP technique has seen widespread circulation. ... -
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node-elm
Backend system based on node.js + Mongodb
node-elm is a Node.js back end that powers the data side of the Ele.me clone ecosystem, complementing the Vue front-end projects. It exposes RESTful endpoints for entities such as restaurants, menus, orders, users, and addresses to simulate a realistic delivery stack. The server demonstrates how to structure a project with routing, controllers, and middleware to keep logic testable and readable. It typically includes authentication flows, input validation, and error handling that mirror... -
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scikit-learn tips
50 scikit-learn tips
scikit-learn-tips is an educational repository that collects practical advice and best practices for using the scikit-learn machine learning library effectively. The project consists of short explanations and examples that highlight common patterns, pitfalls, and techniques used when building machine learning workflows in Python. Each tip typically demonstrates how specific components of scikit-learn, such as pipelines, preprocessing utilities, or model evaluation tools, should be applied in real projects. ... -
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Data Science and Machine Learning Career
Career Resources for Data Science, Machine Learning and Big Data
Data Science and Machine Learning Career is a curated career resource for people pursuing analytical and technical roles. It gathers job platforms, employer review sites, respected courses, competitions, tools, skill areas, and bootcamps in one place. The repository also organizes podcasts for different experience levels and lists common career paths across data science, analytics, engineering, and business intelligence.