Showing 290 open source projects for "programming learning system"

View related business solutions
  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
    Start Free
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB 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.
    Start Free
  • 1
    T81 558

    T81 558

    Applications of Deep Neural Networks

    Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    FFCV

    FFCV

    Fast Forward Computer Vision (and other ML workloads!)

    ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    auto-sklearn

    auto-sklearn

    Automated machine learning with scikit-learn

    auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system. auto-sklearn 2.0 works the same way as regular auto-sklearn. auto-sklearn is licensed the same way as scikit-learn, namely the 3-clause BSD license.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4
    Unitag is a language-independent Unicode-based part-of-speech tagging system. Written entirely in ANSI-compatible C, it should (in theory) compile on any OS, but has been tested on 32-bit Windows.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Fully Managed MySQL, PostgreSQL, and SQL Server Icon
    Fully Managed MySQL, PostgreSQL, and SQL Server

    Automatic backups, patching, replication, and failover. Focus on your app, not your database.

    Cloud SQL handles your database ops end to end, so you can focus on your app.
    Start Free
  • 5
    LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    Mars Framework

    Mars Framework

    Mars is a tensor-based unified framework for large-scale data

    Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 7
    learn-machine-learning-in-two-months

    learn-machine-learning-in-two-months

    Essential Knowledge for learning Machine Learning in two months

    The learn-machine-learning-in-two-months repository is an educational open-source project designed to guide beginners through the process of learning machine learning and deep learning concepts within a structured two-month study plan. The project compiles curated resources, tutorials, and practical notebooks that introduce fundamental topics such as mathematics for machine learning, Python programming, and essential libraries like NumPy and TensorFlow. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 8
    LSTMs for Human Activity Recognition

    LSTMs for Human Activity Recognition

    Human Activity Recognition example using TensorFlow on smartphone

    ...Through the use of sequential neural network architectures, the system learns patterns in motion data that correspond to activities such as walking, sitting, standing, or climbing stairs. The repository includes data preprocessing scripts, neural network architecture definitions, and training pipelines that allow researchers to reproduce and modify the experiments. It serves as an educational example of how deep learning models can process temporal sensor signals for pattern recognition tasks.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 9
    Data Science Collected Resources

    Data Science Collected Resources

    Carefully curated resource links for data science in one place

    Data Science Collected Resources is a curated collection of learning materials and reference links covering a wide range of topics in data science, artificial intelligence, and machine learning. The repository aggregates educational resources from research articles, technical blogs, tutorials, and documentation into a single organized knowledge hub. Its goal is to provide learners and practitioners with easy access to high-quality resources related to data science tools, programming languages, cloud platforms, and machine learning techniques. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

    Learn how to protect your Microsoft 365 data, with simple, actionable tips today.

    Watch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
    Watch Demo Series
  • 10
    Byzer-lang

    Byzer-lang

    A low-code open-source programming language for data pipeline

    Byzer (former MLSQL) is a low-code, open-sourced, and distributed programming language for data pipeline, analytics, and AI in a cloud-native way. Design protocol: Everything is a table. Byzer is a SQL-like language, to simplify data pipeline, analytics, and AI, combined with built-in algorithms and extensions. We believe that everything is a table, a simple and powerful SQL-like language can significantly reduce human efforts of data development without switching different tools.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 11
    DialoGPT

    DialoGPT

    Large-scale pretraining for dialogue

    DialoGPT is an open-source conversational language model developed by Microsoft Research for generating natural dialogue responses using large-scale transformer architectures. The system is built on the GPT-2 architecture and is designed specifically for multi-turn conversation tasks, enabling machines to produce coherent responses during interactive dialogue. The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 12
    Apache TVM

    Apache TVM

    TVM Documentation in Chinese Simplified

    tvm-cn is a community-driven project that provides Chinese documentation for the Apache TVM deep learning compiler stack. Apache TVM is an open-source system designed to optimize and deploy machine learning models efficiently across different hardware platforms such as CPUs, GPUs, and ARM devices. The goal of the repository is to centralize translated learning materials and technical documentation so that Chinese-speaking developers can study the TVM ecosystem more easily. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 13
    Coqui STT

    Coqui STT

    The deep learning toolkit for speech-to-text

    Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure. Effortlessly clone the voices of your talent and have the clone handle the problems...
    Downloads: 6 This Week
    Last Update:
    See Project
  • 14
    SGX-Full-OrderBook-Tick-Data-Trading

    SGX-Full-OrderBook-Tick-Data-Trading

    Providing the solutions for high-frequency trading (HFT) strategies

    SGX-Full-OrderBook-Tick-Data-Trading-Strategy is an open-source research project focused on modeling high-frequency financial market behavior using machine learning techniques. The repository analyzes tick-level order book data from the Singapore Exchange and attempts to capture the dynamics of limit order book movements. By extracting features such as order depth ratios and price movement indicators, the system trains machine learning models to predict short-term market changes. Several algorithms are used during model selection, including Random Forest, Extra Trees, AdaBoost, Gradient Boosting, and Support Vector Machines. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 15
    PySC2

    PySC2

    StarCraft II learning environment

    PySC2 is DeepMind's Python component of the StarCraft II Learning Environment (SC2LE). It exposes Blizzard Entertainment's StarCraft II Machine Learning API as a Python RL Environment. This is a collaboration between DeepMind and Blizzard to develop StarCraft II into a rich environment for RL research. PySC2 provides an interface for RL agents to interact with StarCraft 2, getting observations and sending actions.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 16
    pyntcloud

    pyntcloud

    pyntcloud is a Python library for working with 3D point clouds

    This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 17
    Talking Head Anime from a Single Image

    Talking Head Anime from a Single Image

    Demo for the "Talking Head Anime from a Single Image"

    Talking Head Anime from a Single Image is a machine learning project that demonstrates how neural networks can animate anime characters using only a single input image. The system generates animated facial expressions and movements by applying pose transformations to a static image of an anime character. The underlying model uses deep learning techniques to predict how different facial features and body parts should move based on pose parameters or input signals. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 18
    StudioGAN

    StudioGAN

    StudioGAN is a Pytorch library providing implementations of networks

    ...Among these configurations, we formulate 30 GANs as representatives. Each modularized option is managed through a configuration system that works through a YAML file.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 19
    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 20
    Guia do Cientista de Dados das Galáxias

    Guia do Cientista de Dados das Galáxias

    Repository for gathering information on study materials

    ...Instead of focusing on a single software framework, the project functions as a curated knowledge hub where contributors organize resources into thematic categories such as visualization, machine learning, programming languages, and analytics methodologies. This approach makes it easier for beginners and professionals to discover relevant tools, learning materials, and professional communities.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 21
    CodeSearchNet

    CodeSearchNet

    Datasets, tools, and benchmarks for representation learning of code

    ...The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets.
    Downloads: 3 This Week
    Last Update:
    See Project
  • 22
    The goal of this project is to investigate optimal ways to do genre classification for the ten indigenous South African languages. Funded by Dept of Arts and Culture of the SA Government. http://www.trifonius.co.za/projects/genre-classification
    Downloads: 0 This Week
    Last Update:
    See Project
  • 23
    DeepDanbooru

    DeepDanbooru

    AI based multi-label girl image classification system

    ...The system uses convolutional neural networks trained on large datasets of tagged images to learn relationships between visual features and textual labels. Because the Danbooru dataset contains millions of images with extensive annotations, it provides a valuable training resource for machine learning models specializing in illustration analysis.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 24
    Face Mask Detection

    Face Mask Detection

    Face Mask Detection system based on computer vision and deep learning

    Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 25
    Teachable Machine

    Teachable Machine

    Explore how machine learning works, live in the browser

    Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge. Users can provide example images for different categories, and the system trains a model that learns to classify those inputs in real time. ...
    Downloads: 14 This Week
    Last Update:
    See Project