Repository History
Explore all analyzed open source repositories
big_vision: Google Research's Codebase for Large-Scale Vision Models
big_vision is Google Research's official codebase for training large-scale vision models using Jax/Flax. It has been instrumental in developing prominent architectures like Vision Transformer, SigLIP, and MLP-Mixer. This repository offers a robust starting point for researchers to conduct scalable vision experiments on GPUs and Cloud TPUs, scaling seamlessly from single cores to distributed setups.
NVIDIA Isaac GR00T: A Foundation Model for Generalist Robots
NVIDIA Isaac GR00T N1.6 is an open vision-language-action (VLA) foundation model designed for generalized humanoid robot skills. It enables robots to perform manipulation tasks in diverse environments by taking multimodal input, including language and images. Researchers and professionals can leverage this model for fine-tuning on custom datasets and deploying it for inference.
OmniParser: A Vision-Based Tool for GUI Agent Screen Parsing
OmniParser is a comprehensive tool developed by Microsoft for parsing user interface screenshots into structured, understandable elements. It significantly enhances the ability of vision-based models, such as GPT-4V, to generate accurate actions grounded in specific regions of a GUI. This project aims to advance pure vision-based GUI agents by providing robust screen parsing capabilities.
Memary: The Open Source Memory Layer for Autonomous Agents
Memary is an innovative open-source memory layer designed to enhance autonomous agents by emulating human memory. It integrates knowledge graphs and memory modules to provide agents with advanced capabilities for reasoning and learning. This project aims to make agents more intelligent and capable of self-improvement.
GenerativeAICourse: A Comprehensive Hands-On Generative AI Engineering Course
This repository offers a comprehensive, hands-on Generative AI course, starting from fundamental AI concepts to building production-grade applications. It focuses on AI engineering, covering topics like LLMs, RAG, AI agents, and prompt engineering with practical tutorials. The course aims to equip learners with the skills needed to build real-world AI solutions.
DataScienceInteractivePython: Interactive Dashboards for Learning Data Science
DataScienceInteractivePython is a GitHub repository by Professor Michael Pyrcz, offering interactive Python dashboards designed to simplify the learning process for data science concepts. It provides hands-on tools for students and enthusiasts to explore statistics, models, and theoretical concepts through engaging, interactive examples. This resource aims to remove barriers to education by allowing users to experiment with data analytics and machine learning in real-time.
FinRL-Trading: Deep Reinforcement Learning for Automated Stock Trading
FinRL-Trading is a powerful GitHub repository built upon the FinRL framework, designed to develop advanced AI stock-selection and trading strategies. It leverages both Supervised Learning and Deep Reinforcement Learning to create robust models, with capabilities extending to deployment on online trading platforms. This project offers a comprehensive approach to algorithmic trading, from data processing to live paper trading.
FinRL: Financial Reinforcement Learning Framework for Automated Trading
FinRL is the first open-source framework for financial reinforcement learning, providing an ecosystem for automated trading in quantitative finance. It offers a comprehensive pipeline, various DRL algorithms, and support for multiple market environments and data sources, making it a powerful tool for researchers and practitioners.
FinGPT: Open-Source Large Language Models Revolutionizing Financial AI
FinGPT is an open-source initiative providing large language models specifically designed for the financial sector. It aims to democratize access to advanced AI for finance, offering cost-effective and adaptable solutions for tasks like sentiment analysis and robo-advisory, addressing the dynamic nature of financial data.