Search Results for "repository" - Page 31
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Showing 1010 open source projects for "repository"
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Albedo
A recommender system for discovering GitHub repos
Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible... -
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Think Bayes
Code repository for Think Bayes
...The book and code encourage thinking in terms of discrete approximations (sums over distributions) rather than continuous integrals, making it more accessible to many programmers. Over time, the repository has been updated (including a second edition version) to reflect improved practices, corrections, and modern Python tooling. -
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GPT2 for Multiple Languages
GPT2 for Multiple Languages, including pretrained models
With just 2 clicks (not including Colab auth process), the 1.5B pretrained Chinese model demo is ready to go. The contents in this repository are for academic research purpose, and we do not provide any conclusive remarks. Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC) Simplifed GPT2 train scripts（based on Grover, supporting TPUs). Ported bert tokenizer, multilingual corpus compatible. 1.5B GPT2 pretrained Chinese model (~15G corpus, 10w steps). ... -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
...It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD, and CIFAR-10. In addition to core GAN training, the repository includes tools for model evaluation, such as Inception Score and SWD metrics, as well as advanced features like GDPP for diverse generation and AC-GAN conditioning for class-specific synthesis. The framework also supports “inspirational generation,” enabling style or content transfer from reference images through pre-trained models. -
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BPF Performance Tools
Official repository for the BPF Performance Tools book
...The repository showcases how eBPF enables safe, low-overhead tracing directly inside the Linux kernel without requiring intrusive instrumentation. It includes tools for profiling, latency analysis, syscall tracing, and troubleshooting distributed systems or production environments. Overall, the project is regarded as a foundational resource for understanding advanced Linux performance engineering and observability techniques. -
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StarGAN
Official PyTorch Implementation
...Overall, the repository provides a clean and practical baseline for experimenting with multi-domain generative modeling in PyTorch. -
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
...It introduces a hierarchical latent model, where high-level intents are first clustered and then translated into coherent language, improving dialogue diversity and goal consistency. The repository also includes the Negotiate dataset, comprising over 5,800 dialogues across 2,200 unique scenarios. -
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Retro
Retro Games in Gym
...This design improves factual accuracy, reduces hallucinations, and enables smaller models to perform comparably to much larger ones by leveraging retrieval. The repository provides code and resources for training and evaluating RETRO models, along with infrastructure for integrating retrieval into the transformer pipeline. It includes example configurations, datasets, and utilities for building retrieval-augmented generation systems. RETRO represents an important step toward combining large-scale language modeling with information retrieval, offering researchers a foundation to study hybrid approaches for scaling AI responsibly. -
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NLP Best Practices
Natural Language Processing Best Practices & Examples
...Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and best practices for building NLP systems, provided as Jupyter notebooks and utility functions. The focus of the repository is on state-of-the-art methods and common scenarios that are popular among researchers and practitioners working on problems involving text and language. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems. -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
...On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple models with a PyTorch-like feel, including multilayer perceptrons. The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. It is commonly used as a learning bridge between basic calculus intuition and full-scale deep learning frameworks, helping developers understand why autodiff libraries behave the way they do. -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. ... -
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NLP-progress
Repository to track the progress in Natural Language Processing (NLP)
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. -
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sysadmin-util
Tools for Linux/Unix sysadmins
sysadmin-util is a compact collection of small, practical command-line utilities gathered for everyday system administration tasks. The repository contains a variety of single-purpose scripts that solve common problems such as determining file ages, testing SSH connectivity, checking MySQL slave status, expanding IPv6 addresses, sending metrics to Graphite, and working with IP ranges. The project intentionally keeps the set small and focused, emphasising quality and personal usefulness over trying to be a large toolbox everyone adopts unchanged. ... -
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RL-Stock
Automated stock trading through a simulated training environment
...The project includes scripts for collecting stock data, defining a reinforcement learning environment, training an agent, and visualizing results. It focuses on how an agent can learn trading-like behavior through rewards, states, and actions. The repository is useful for learners who want to connect reinforcement learning concepts with a familiar financial market example. Its main value is demonstrating the structure of a deep reinforcement learning trading experiment while making clear that real-world investing requires much more validation and risk control. -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
SageMaker Chainer Containers is an open-source library for making the Chainer framework run on Amazon SageMaker. This repository also contains Dockerfiles which install this library, Chainer, and dependencies for building SageMaker Chainer images. Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python version and processor type. ... -
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Coronavirus Tracker API
API for tracking the global coronavirus (COVID-19, SARS-CoV-2)
...To view timelines of cases by US counties use ?source=nyt&timelines=true. Currently, 3 different data sources are available to retrieve the data. Worldwide Data repository operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). U.S. County data that comes from the Conference of State Bank Supervisors. The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States. This API provides the timeseries at the US county level. jhu data-source will be used as a default source if you don't specify a source parameter in your request. ... -
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VGGFace2
VGGFace2 Dataset for Face Recognition
...It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc. -
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Top deep learning Github repositories
Top 200 deep learning Github repositories sorted by stars
Top-Deep-Learning is a curated repository that aggregates some of the most influential and widely used deep learning projects available on GitHub. Instead of providing its own machine learning models or frameworks, the project functions as an organized index that helps users discover high-quality deep learning repositories across different application domains. The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning, and other areas of artificial intelligence. ... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. -
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PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
...It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve tractable likelihood-based training. It also includes scripts for reproducing key experimental results from the paper, such as conditional sampling on datasets like CIFAR-10. The project serves as both a research reference and a practical framework for experimenting with autoregressive generative models. ... -
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cocoNLP
A Chinese information extraction tool
...Because it aims at utility over complexity, it’s useful for prototyping data products or building lightweight text analytics where large models would be overkill. The repository also includes examples and test snippets to help you understand expected inputs and typical outputs, which shortens the learning curve for newcomers. -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization strategies, and data processing techniques. ... -
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Machine Learning with TensorFlow
Accompanying source code for Machine Learning with TensorFlow
...The repository includes implementations of algorithms such as logistic regression, convolutional neural networks, and autoencoders, which allow readers to experiment with different learning techniques. Many examples are structured as standalone scripts or notebooks that can be executed directly to reproduce the results described in the book. -
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Flask-GraphQL
Adds GraphQL support to your Flask application
Adds GraphQL support to your Flask application. This will add /graphql endpoint to your app and enable the GraphiQL IDE. If you are using the Schema type of Graphene library, be sure to use the graphql_schema attribute to pass as schema on the GraphQLView view. Otherwise, the GraphQLSchema from graphql-core is the way to go. The GraphQLSchema object that you want the view to execute when it gets a valid request. A value to pass as the context_value to graphql execute function. By default is... -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab.