1. Data preprocessing
  2. ML-Component Development
  3. Open Source Tools for AI-Projects

Open Source Tools for AI-Projects

Displaying 1 - 10 of 50
airflow by apache


Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
pytorch by pytorch


Tensors and Dynamic neural networks in Python with strong GPU acceleration
arrow by apache


Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
argo-workflows by argoproj


Workflow engine for Kubernetes
cudf by rapidsai


cuDF - GPU DataFrame Library
dask by dask


Parallel computing with task scheduling
transformers by huggingface


🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
metaflow by Netflix


:rocket: Build and manage real-life data science projects with ease!
h2o-3 by h2oai


H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
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.