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A PyTorch Library for Meta-learning Research
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Hyper-parameter optimization for sklearn
Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
The main features of microsoft/archai are: Automated Machine Learning, Developer Tools.
Projects with overlapping indexed features include: ray-project/ray — Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting… hyperopt/hyperopt-sklearn — Hyper-parameter optimization for sklearn. learnables/learn2learn — A PyTorch Library for Meta-learning Research. determined-ai/determined — Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning,… karpathy/autoresearch — Autoresearch is an autonomous machine learning research agent and architecture search framework. It employs a… autogluon/autogluon — AutoGluon is an automated machine learning framework and multimodal library designed to automate the end-to-end…