Explaining the predictions of any machine learning classifier.
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A comprehensive toolkit to build Machine Learning applications with Rust.
Build, train, and ship custom machine learning models using an easy visual interface.
Class on machine w/ PDF, lectures, code.
Machine Learning library for the web, Node.js and developers.
Machine learning for language toolkit.
A model-agnostic visual debugging tool for machine learning.
A Julia package for manifold learning and nonlinear dimensionality reduction.
Application-oriented deep reinforcement learning framework addressing real-world decision problems.
A production-ready library for multicalibration, fairness, and bias correction in machine learning models.
A blog about open source software, graph databases, cloud native architectures, information theory, artificial intelligence, and machine learning.
MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
A platform for deploying and serving machine learning models.
Flexible Deep Learning Framework in Julia.
An open source robotics benchmark for meta- and multi-task reinforcement learning.
A distributed machine learning framework Apache Spark.
List of several machine learning libraries.
MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
All-in-one web-based IDE specialized for machine learning and data science.
Machine learning and numerical analysis tools for Node.js and the Browser!
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Friendly machine learning for the web!
A set of functions to support the development of machine learning algorithms.