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Strategies for managing big data

There are many different approaches for how to handle data that won't fit in memory on a single machine.

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Host a Jupyter Notebook as an API

Do you have a Jupyter Notebook that you want to run every time an API is called? You can do that with Saturn Cloud jobs.

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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 …

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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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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 …

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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 …

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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!

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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.

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