Dask Video Tutorial

Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love.

In this 90 minute tutorial we will cover an overview of Dask including dataframes, arrays, machine learning and distributed scheduling.

Install and run this tutorial

# Clone the repo
git clone https://github.com/jacobtomlinson/dask-video-tutorial.git

# Go to the repo directory
cd dask-video-tutorial

# Create a new Python environment however you prefer
# e.g
# python -m venv dask-tutorial
# source dask-tutorial/bin/activate

# Install the dependencies
pip install dask[complete] dask-ml jupyterlab dask-labextension ipycytoscape

# Start Jupyter Lab
jupyter lab

Schedule

These are the rough timings for the tutorial.

• Overview of Dask with Dask Dataframe (10 mins)
• Introductory Lab (10 mins) and results (5 mins)
• Dask GUI and dashboards (10 mins)
• Dask Array (10 mins)
• Dask ML with lab (10 mins) and results (5 mins)
• Bags and Futures (10 mins)
• Distributed (10 mins)
• Wrapup and close (5 mins)