🚀 Build and manage real-life data science projects with ease!
Alternatives To Metaflow
Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Keras59,4475786 hours ago80June 27, 2023100apache-2.0Python
Deep Learning for humans
Scikit Learn55,99618,9449,7556 hours ago71June 30, 20232,260bsd-3-clausePython
scikit-learn: machine learning in Python
Ml For Beginners53,637
7 days ago7mitHTML
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Made With Ml34,217
4 days ago5May 15, 20194mitJupyter Notebook
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Ray27,966802988 hours ago87July 24, 20233,451apache-2.0Python
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Streamlit27,572178986 hours ago204July 20, 2023671apache-2.0Python
Streamlit — A faster way to build and share data apps.
Spacy27,2441,5331,1987 hours ago222July 07, 202394mitPython
💫 Industrial-strength Natural Language Processing (NLP) in Python
Data Science Ipython Notebooks25,242
3 months ago34otherPython
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Lightning24,74076206 hours ago253July 25, 2023688apache-2.0Python
Deep learning framework to train, deploy, and ship AI products Lightning fast.
Applied Ml24,714
23 days ago3mit
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Alternatives To Metaflow
Select To Compare

Alternative Project Comparisons



Metaflow is a human-friendly library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

For more information, see Metaflow's website and documentation.

From prototype to production (and back)

Metaflow provides a simple, friendly API that covers foundational needs of ML, AI, and data science projects:

  1. Rapid local prototyping, support for notebooks, and built-in experiment tracking and versioning.
  2. Horizontal and vertical scalability to the cloud, utilizing both CPUs and GPUs, and fast data access.
  3. Managing dependencies and one-click deployments to highly available production orchestrators.

Getting started

Getting up and running is easy. If you don't know where to start, Metaflow sandbox will have you running and exploring Metaflow in seconds.

Installing Metaflow in your Python environment

To install Metaflow in your local environment, you can install from PyPi:

pip install metaflow

Alternatively, you can also install from conda-forge:

conda install -c conda-forge metaflow

If you are eager to try out Metaflow in practice, you can start with the tutorial. After the tutorial, you can learn more about how Metaflow works here.

Deploying infrastructure for Metaflow in your cloud

While you can get started with Metaflow easily on your laptop, the main benefits of Metaflow lie in its ability to scale out to external compute clusters and to deploy to production-grade workflow orchestrators. To benefit from these features, follow this guide to configure Metaflow and the infrastructure behind it appropriately.


Slack Community

An active community of thousands of data scientists and ML engineers discussing the ins-and-outs of applied machine learning.


Generative AI and LLM use cases

Get in touch

There are several ways to get in touch with us:


We welcome contributions to Metaflow. Please see our contribution guide for more details.

Popular Data Science Projects
Popular Machine Learning Projects
Popular Data Processing Categories
Related Searches

Get A Weekly Email With Trending Projects For These Categories
No Spam. Unsubscribe easily at any time.
Machine Learning
Data Science
Reproducible Research
High Performance Computing