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- OpenML
OpenML is an open platform for sharing datasets, algorithms, and experiments - to learn how to learn better, together
- Open Machine Learning
How to use OpenML¶ OpenML is accessible to a wide range of people: Explore the OpenML website to discover, download and upload ML resources Install an OpenML library to access and share resources programmatically through our APIs Select one of the detailed guides in the top menu
- OpenML - Open Machine Learning
OpenML is entirely open and you do not need an account to access data (rate limits apply) However, signing up via the OpenML website is very easy (and free) and required to upload new resources to OpenML and to manage them online
- OpenML
OpenML automatically versions and analyses each dataset and annotates it with rich meta-data to streamline analysis Easily search thousands of datasets and import them directly into your code or toolboxes, or quickly find similar datasets together with the best machine learning approaches
- OpenML
Built around open interfaces, OpenML can be used to automatically share (and import) datasets, algorithms, and experiments results straight from the tools that we already know and love Through our APIs, OpenML can be easily integrated into new workflows and processes, to import new data and export new results
- OpenML in 10 minutes - Open Machine Learning
OpenML in 10 minutes¶ This page will guide you through the process of getting started with OpenML While this page is a good starting point, for more detailed information, please refer to the integrations section and the rest of the documentation
- Using datasets - Open Machine Learning - docs. openml. org
import openml # Get dataset by ID dataset = openml datasets get_dataset (61) # Get dataset by name dataset = openml datasets get_dataset ('Fashion-MNIST') # Get the data itself Returns a pandas dataframe by default
- Creating datasets - Open Machine Learning - docs. openml. org
If you can load a dataset in common data structures (e g a pandas dataframe), you can upload it to OpenML in a few lines of code, and OpenML will automatically store it in efficient data formats Vice versa, you can download any OpenML dataset directly into common machine learning libraries
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