Multi-GPU TensorFlow on Saturn Cloud
If your machine has multiple GPUs you can train a TensorFlow model across all of the GPUs at once.
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If You Can Write Functions, You Can Use Dask
Many data scientists don't know where to start with the distributed framework Dask. Good news--it's often no more work than just writing a Python function.
Read article →Speeding up Neural Network Training With Multiple GPUs and Dask
By combining Dask and PyTorch you can easily speed up training a model across a cluster of GPUs. But how much of a benefit does that …
Dealing with Long Running Jupyter Notebooks
Jupyter struggles with long running notebooks--one hiccup in your connection and the execution can cancel. Here is a solution to manage …
Just Start with the Dask LocalCluster
You can get lots of value from Dask without even using a distributed cluster. Try using the LocalCluster instead!
Deploy Your Machine Learning Model - Part 3 (Flask API or Web App)
In the final part of this three part series we cover how to take a trained model and deploy it as an API.
Deploy Your Machine Learning Model - Part 2 (Voila Web App)
In part two of this three part series we cover how to take a trained model and make an interactive web app from it.
Deploy Your Machine Learning Model - Part 1 (The Model)
In part one of this three part series we cover how to train a model to deploy as a dashboard or API.
Deploying Data Pipelines at Saturn Cloud with Dask and Prefect
How you can automate your complex tasks using Saturn Cloud, Dask, and Prefect
Easily Connect to Dask from Outside of Saturn Cloud
While Saturn Cloud provides client resources to connect to Dask clusters, you can also directly connect from external locations.