Popular GitHub Repositories for 081203m05009h

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

TinyML AI inference library

Tutorials and training material for the H2O Machine Learning Platform

A curated list of gradient boosting research papers with implementations.

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

将EPUB、PDF和文本文件转换成带同步字幕的有声书。

Auto-Update your M3U Playlists every day without needing an app, with the same link.

Large-Scale Visual Representation Model

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

H2O.ai Machine Learning Interpretability Resources

An all-in-one AI audio playground using Cloudflare AI Workers to transcribe, analyze, summarize, and translate any audio file.

Providing reproducibility in deep learning frameworks

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

A curated list of research, applications and projects built using the H2O Machine Learning platform

Run larger LLMs with longer contexts on Apple Silicon by using differentiated precision for KV cache quantization. KVSplit enables 8-bit keys & 4-bit values, reducing memory by 59% with <1% quality loss. Includes benchmarking, visualization, and one-command setup. Optimized for M1/M2/M3 Macs with Metal support.

? Kokoro Web: Free AI text-to-speech, online or self-hosted, OpenAI compatible!

VoxNovel: generate audiobooks giving each character a different voice actor.

TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)