Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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:zap: A Fast, Extensible Progress Bar for Python and CLI
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
A hyperparameter optimization framework
NumPy aware dynamic Python compiler using LLVM
Asynchronous parallel SSH client library.
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Gzip Decompression and Random Access for Modern Multi-Core Machines
Parallel uploads to Amazon AWS S3
40K, small memory footprint, single binary that run list of commands in parallel and waits for their termination
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.