Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Awesome Android Reverse Engineering is a GitHub repository or organization with source code, releases, documentation, or project resources.
Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
A framework for performing reproducible AI and ML for Weights and Biases.
Code and documentation to train Stanford's Alpaca models, and generate the data.
Curated list of top Hugging Face models for NLP, vision, and audio tasks with demos and benchmarks.
List of awesome compiler projects and papers for tensor computation and deep learning.
Python library for data-centric AI and machine learning with messy, real-world data and labels.
A Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.
Track, log, visualize and evaluate your LLM prompts and prompt chains.
A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
A fast and multi-purpose DNS toolkit from ProjectDiscovery for running DNS probes, resolving records and filtering DNS responses.
E-commerce skills for AI agents — product research, marketing automation, supply chain optimization, and business analytics for online sellers across Amazon, Shopify, Etsy, TikTok Shop, and all platforms.
AI Agent Teams for multi-app social media marketing — automated trend research, content creation, optimization, publishing, and analytics across TikTok, Instagram, YouTube, Facebook, Reddit, X, and Pinterest
A Clojure library of optimisation and control theory tools and convenience functions based on Neanderthal.
C, C++, and Python tools for named entity recognition and relation extraction.
Machine learning and numerical analysis tools for Node.js and the Browser!
OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others).
CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
A platform for reproducible and scalable machine learning and deep learning on kubernetes.
Open-source tool to simplify the process of creating and managing LLM workflows and prompts as a self-hosted solution.