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A little curiosity. A world of open source.
THE FIRST COLLECTIONA large collection of research code and datasets released by Google Research, covering machine learning, AI, and scientific computing projects. Users can download individual subdirectories instead of cloning the whole repository.
Optuna is an automatic hyperparameter optimization framework designed for machine learning, featuring a define-by-run API for dynamic search space construction.
An open-source UFC fight prediction project: Elo ratings, a gradient-boosted ensemble and a multi-task neural network blended into one calibrated scorer, evaluated by expanding-window walk-forward over 2018-2026, with a Streamlit matchup explorer and a weekly self-updating data pipeline.
A curated list of machine learning frameworks, libraries, and software organized by programming language and topic—a useful index for researchers and developers exploring ML tools.
Reinfors is a high-throughput reinforcement-learning library that runs game dynamics, search, and episode orchestration in parallel Rust, while keeping Python-based networks and training entirely under the caller's control.
NVIDIA Apex is a PyTorch extension providing mixed precision (AMP) and distributed training utilities, plus optional C++/CUDA fused kernels for optimizers, normalization, and parallelism.
An educational repository teaching supervised machine learning from first principles using Python, covering mathematical foundations and practical implementations.
Open LLM hallucination benchmark regarding the BNCC (Brazil's National Common Curricular Base). It measures how much models invent official codes and texts using an auditable methodology with raw data and CI.
Eclipse Deeplearning4J (DL4J) is a JVM-based deep learning ecosystem supporting Java, Scala, Kotlin, and more. It includes model import from Keras, TensorFlow, ONNX; ND4J for linear algebra; SameDiff for automatic differentiation; DataVec for ETL; and runs on CPU/GPU across Windows, Linux, macOS.
Dive into LLMs is a free, public-welfare programming tutorial series by Shanghai Jiao Tong University, covering 11 core LLM topics including fine-tuning, prompt learning, knowledge editing, math reasoning, watermarking, jailbreak attacks, steganography, multimodal models, GUI agents, agent safety, and RLHF alignment, with slides, guides, and runnable scripts.
Made With ML is an open-source course and codebase teaching how to design, develop, deploy and iterate on production-grade machine learning applications, covering MLOps, testing, serving, CI/CD and continual learning.
PolyOCR Service is a multi-language OCR service built on PaddleOCR 3.x, supporting recognition for 78 languages, optional translation capabilities, and a standalone PaddleOCR-VL service.
Colossal-AI is an open-source system for training and running large AI models more cheaply and efficiently, offering parallel training strategies, memory management, and inference acceleration for LLMs, diffusion models, and more.
Microsoft's 10-week, 20-lesson data science curriculum for beginners, with project-based lessons, quizzes, and 50+ language translations.
Official code repository for 'Build a Large Language Model (From Scratch)': step-by-step PyTorch implementation of GPT-like models, covering pretraining and finetuning with notebooks and exercises.
GramGuidedURA provides code for semi-blind channel estimation in Unsourced Random Access (URA) using Gram-guided diffusion models.
fastai is a deep learning library built on PyTorch that provides both high-level components for rapid productivity and low-level components for research and customization.
FiftyOne is an open-source tool for building high-quality datasets and computer vision models. It enables users to visualize, label, evaluate, and curate visual AI data.
JouleWise is a benchmarking harness designed for the flexible power analysis of LLM inference workloads, focusing on auditable energy and latency measurement.
Iris is a local-first MCP server that scores AI agent runs for quality, safety, and cost using 20 built-in deterministic rules, an optional LLM judge, and a web dashboard — all on your machine with no account or telemetry.
