Repository History
81 repositories tagged with Machine Learning
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.
multiresolution-time-series-transformer: Long-term Forecasting with MTST
This repository provides a PyTorch implementation of the Multi-Resolution Time-Series Transformer (MTST) for long-term forecasting. Based on the Zhang et al. (2024) paper, MTST processes temporal data at different resolutions to effectively capture both short-term and long-term patterns. It offers a flexible and robust solution for advanced time series prediction tasks.
Subwiz: A Lightweight GPT Model for Subdomain Discovery
Subwiz is an innovative, lightweight GPT model designed specifically for discovering subdomains. It leverages a transformer architecture, trained on extensive subdomain lists, to predict new subdomains efficiently. This tool is ideal for security researchers and developers looking to expand their subdomain enumeration capabilities.
txtinstruct: Building Instruction-Tuned Models with Custom Data
txtinstruct is a Python framework designed for training instruction-tuned models. It focuses on supporting open data and models, enabling users to build their own instruction-following datasets and train models without licensing ambiguity. This project simplifies the process of creating custom instruction-tuned solutions.
deepface: Lightweight Face Recognition and Facial Attribute Analysis Library
deepface is a powerful yet lightweight Python library for face recognition and facial attribute analysis. It offers capabilities for age, gender, emotion, and race prediction, wrapping state-of-the-art models for robust performance. Developers can easily integrate advanced facial analysis into their applications with just a few lines of code.
mlx-examples: Practical Examples for the MLX Machine Learning Framework
mlx-examples is a comprehensive GitHub repository showcasing a variety of standalone examples built using the MLX framework. It provides practical implementations across text, image, audio, and multimodal models, serving as an excellent resource for developers exploring MLX. This collection helps users understand and apply MLX for diverse machine learning tasks.
Open R1: An Open-Source Reproduction of DeepSeek-R1 for Advanced LLM Training
Open R1 is a Hugging Face project dedicated to creating a fully open reproduction of DeepSeek-R1, a powerful reasoning language model. This initiative provides comprehensive tools and recipes for training, evaluating, and generating data for large language models. It fosters community collaboration in AI research, enabling developers to build upon and understand the complex R1 pipeline.
llama-cpp-python: Python Bindings for llama.cpp
llama-cpp-python provides robust Python bindings for the popular llama.cpp library, enabling efficient local inference with large language models. It offers a high-level API compatible with OpenAI's API, facilitating easy integration into existing applications. The project also includes a powerful web server for local deployment and supports various hardware acceleration backends.
FuncVul: Function-Level Vulnerability Detection with LLMs and Code Chunks
FuncVul is an innovative model designed to detect vulnerabilities at the function level in C/C++ and Python code, addressing a critical gap in software supply chain security. By leveraging large language models (LLMs) and a code chunk-based approach, FuncVul significantly improves the precision of vulnerability identification. The model demonstrates superior performance compared to existing state-of-the-art methods, achieving high accuracy and F1 scores across various datasets.
FlashVideo: Efficient High-Resolution Video Generation with Flowing Fidelity
FlashVideo is an innovative GitHub repository that introduces a novel approach for efficient high-resolution video generation. It leverages a two-stage diffusion model to produce detailed videos, scaling from 270p to 1080p. This project focuses on maintaining fidelity to detail while significantly improving the efficiency of the video generation process.
Weave by Weights & Biases: A Toolkit for AI-Powered Applications
Weave is an open-source toolkit developed by Weights & Biases designed for building and managing AI-powered applications. It provides robust features for logging, debugging, and evaluating language model inputs and outputs, streamlining the development workflow for generative AI. Weave aims to bring rigor and best practices to the experimental process of AI software development.