Effective Machine Learning with Dask

This class focuses on leveraging Dask for Machine Learning in several different ways: Dask implements a number of distributed algorithms; interoperates with popular Python libraries, and integrates with several external projects (e.g., PyTorch). This module looks at each of the options, as well as the full ML lifecycle, from ingesting data to performing inference.

Learn Ideas and Gain Skills

Duration: half-day or full day

Prerequisites

Topics

Introduction

Dask and scikit-learn

Data Preparation and Dask’s Algorithms and Integration with XGBoost

Performing Inference at Scale

Custom Algorithms (Optional Intro, full-day only)

Review and Q&A