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UC San Diego Jupyterhub (Data Science) Platform


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Student Resources

Faculty Resources

Overview

UC San Diego's Data Science/Machine Learning Platform (DSMLP) provides undergraduate and graduate students with access to research-class CPU/GPU resources for coursework, formal independent study, and student projects.
Instructors may request Datahub/DSMLP for their courses via an Instructional Technology Request (CINFO), with students automatically receiving access 1-2 days prior to start of each term. Access to Datahub/DSMLP is described in the ITS Instructional Technology Guides.

Jupyter Notebooks

Web-based Jupyter notebooks allow students to combine live code, equations, visualizations and narrative text for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and more.  DSMLP's Jupyter notebooks offer straightforward interactive access to popular languages and GPU-enabled frameworks such as Python, R, Pandas, PyTorch, TensorFlow, Keras, NLTK, and AllenNLP.

Machine Learning

Complex ML workflows are supported through terminal/SSH logins, background batch jobs, and a full Linux/Ubuntu CUDA development suite.  Users may install additional library packages (e.g. conda/pip, CRAN) as needed, or can opt to replace the default environment entirely by launching their own custom Docker containers.

High-speed cluster-local storage houses student workspaces, course files, and common training corpora (e.g. CIFAR, ImageNet).

If you would like to acknowledge this service in any publications, please use the text below.

The Data Science and Machine Learning Platform is operated by IT Services (ITS), with additional financial contributions from Cognitive Science and Jacobs School of Engineering