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ML.NET is an open source and cross-platform machine learning framework for .NET.

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Instant Kubernetes-Native Application Observability

Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

A hyperparameter optimization framework

Streamlit — A faster way to build and share data apps.

The Julia Programming Language

A Cloud Native Batch System (Project under CNCF)

Probabilistic reasoning and statistical analysis in TensorFlow

scikit-learn: machine learning in Python

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

The open source developer platform to build AI agents and models with confidence. Enhance your AI applications with end-to-end tracking, observability, and evaluations, all in one integrated platform.