🤓 StartupSpotter 🤓
They call themselves
‘creative bunch of data nerds‘
orchest.io
Build pipelines iteratively by editing and connecting notebooks and scripts.
@RickLamers and github.com/yannickperrenet 👋
are the Co-Founders of this 🔥 Startup!
They call themselves
‘creative bunch of data nerds‘
orchest.io
Build pipelines iteratively by editing and connecting notebooks and scripts.
@RickLamers and github.com/yannickperrenet 👋
are the Co-Founders of this 🔥 Startup!
Jupyter notebooks are a dominant tool for data scientists, but they lack a number of conveniences for building reusable and maintainable systems.
orchest.io
No frameworks. No YAML.
Just write your data processing code directly
in Python, R, Julia or Bash.
No frameworks. No YAML.
Just write your data processing code directly
in Python, R, Julia or Bash.
For machine learning projects in particular there is a need for being able to pivot from exploring a particular dataset or problem to integrating that solution into a larger workflow.
Rick Lamers and Yannick Perrenet were tired of struggling with one-off solutions when they created the Orchest platform.
Orchest allows you to turn your notebooks into executable components that are integrated into a graph of execution for running end-to-end machine learning workflows.
Creating a pipeline from scratch:
orchest.io/video-tutorials
orchest.io/video-tutorials
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