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A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.
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Roadmap to becoming an Artificial Intelligence Expert.
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A comprehensive set of fairness metrics for datasets and machine learning models.
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Code for Data Science at Olin College, Spring 2014.
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Approximate nearest neighbours implementation.
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Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
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AutoML framework & toolkit for machine learning on graphs.
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Automated machine learning for image, text, tabular, time-series, and multi-modal data.
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AutoKeras goal is to make machine learning accessible for everyone.
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Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
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Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis).
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A curated list of machine learning models in CoreML format.
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Curated list of federated learning publications, re-organized from Arxiv (mostly).
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Curated list of ML related resources for Ruby.
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Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
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CPU and GPU-accelerated Machine Learning Library.
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Neural networks in JavaScript - continued community fork of Brain.
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Fast, flexible and fun neural networks. This is the successor of PyBrain.
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Fast open framework for deep learning.
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Torch-like deep learning framework for Javascript with support for tensors, autograd, optimizers, and other neural net constructs.
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Implementation of Random Forest in Common Lisp.
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Python library for data-centric AI and machine learning with messy, real-world data and labels.
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Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.
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A machine learning library for Clojure built on top of Weka and friends.