1. ML-Component Development
  2. Model hyperparameter & architecture search
  3. Open Source Tools for AI-Projects

Open Source Tools for AI-Projects

Displaying 1 - 10 of 32
ray by ray-project


An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
DeepSpeed by microsoft


DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
determined by determined-ai


Determined: Deep Learning Training Platform
Neuraxle by Neuraxio


A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.
tfx by tensorflow


TFX is an end-to-end platform for deploying production ML pipelines
autogluon by awslabs


AutoGluon: AutoML for Image, Text, and Tabular Data
nni by microsoft


An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
keras-tuner by keras-team


Hyperparameter tuning for humans
auto-sklearn by automl


Automated Machine Learning with scikit-learn
autokeras by keras-team


AutoML library for deep learning