Workshop: Scaling Machine Learning in Python
In this hands-on workshop, you'll have the opportunity to see how a standard data science and machine learning workflow, using pandas and scikit-learn, can easily be parallelized using Dask clusters. Instructors will walk step-by-step through how to migrate existing Python code to Dask, an open-source framework enabling parallelization of Python.
The workshop will take place within Saturn Cloud Hosted, which you can sign up for free here: https://www.saturncloud.io/s/tryhoste...
Our platform enables quick and easy access to parallel computing in Python. Join us to get hands-on experience using Saturn Cloud and learn what you need to confidently scale up your own machine learning.
After this workshop, you will know:
- When you need parallel computing for your workflow
- How to use Dask Dataframes for loading and cleaning data
- How to perform distributed model training with Dask
- How to scale a hyperparameter search across a cluster
- How to conduct a batch inference task over a cluster
*To get the full learning value from this workshop, attendees should have prior experience with machine learning in Python. Experience with parallel computing is not needed.
*Please ensure your internet connection is strong and you're in an undistracted space so you can interact with the rest of the group.
Github Repo: https://github.com/saturncloud/worksh...
Join the Slack community here to ask any questions: https://join.slack.com/t/saturn-commu...