Have you checked https://dvc.org/ ?

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git for versioning code

dvc for versioning data (and other ML things)

mlflow for managing ml pipelines (overlaps with some parts of dvc)

conda for environment management (yes, it can be slow...)

Try mamba if you struggle with conda being slow, its a drop in replacement.

Yes, it's true. I have not tried using mamba with mlflow - maybe it integrates, maybe it doesn't. MLflow docs at the time of my reading indicated it works with conda or docker only.

Why is this downvoted? Seems like a decent question.

The keyword you want, similar to DevOps where Github plays a role as the code storage, is MLOps, and within that you want to look for data and model management and versioning. There are quite a number of companies offering various aspects of that, see for example this random infographic: https://adataanalyst.com/wp-content/uploads/2021/05/Infra-Tooling3.png

Check out Dagshub!

huggingface

Comet.ml does everything you listed! Free for individuals!

https://wandb.ai/site - Weights & Biases does everything you listed, from versioning code, datasets and models to vizualizing experiments and managing hyperparameters and even running hyperparameter search. It can be used to fully reproduce and recreate the entire state of your ML workflow. It's free for individuals and academics.

I can’t believe nobody has mentioned MLFlow

Is there no platform which does it all? Would WandB cut it?

>https://adataanalyst.com/wp-content/uploads/2021/05/Infra-Tooling3.png

Understood! Thanks so much for that - also wanted to understand at core the thinking process of an ML engineer - what parameters do they prioritise while choosing a tool - like user experience or service? lot of features or just few quality features done well?

databricks is a platform that does it all. but technically, Azure, AWS, and GCP all do it too

Also, does any one of them do automatic versioning?

Yes, but it needs to be configured a lot. Also, does it do automatic data versioning everytime it detects a major change or we need to commit each time?

Check mymlops.com

wandb is great but I had no idea it also versioned code, I'm still using git for that.

https://docs.wandb.ai/ref/app/features/panels/code#save-library-code. it's turned off by default for security and privacy reasons. But it can be enabled or you can optionally log code in individual projects or runs.

+1 for Dagshub

GitLab is an open-source and free alternative to GitHub for hosting ML projects and code. It's used by many organizations for software development, data analysis, and machine learning. It offers a wide range of features, including an integrated CI/CD pipeline, version control, issue tracking, and project management. Additionally, GitLab also supports Jupyter Notebooks and data science projects.