Upcoming Events

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Events Archive

Introduction to the Machine Learning Libraries

The Princeton HPC clusters offer several machine learning (ML) software libraries. Some are straightforward to use while others need to be installed and are highly configurable. Additional complications arise when job scheduler scripts need to be written to take advantage of multi-threading and/or GPUs.


Intro to Data Analysis using Python

This workshop will get students started in data analysis using the pandas Python package. It will briefly cover different components of data analysis and connect them with the goal of extracting meaning from data. We will go over an example to illustrate the data analysis process from beginning to end.


Consistency of Cheeger cuts: Total Variation, Isoperimetry, and Clustering

Clustering unlabeled point clouds is a fundamental problem in machine learning. One classical method for constructing clusters on graph-based data is to solve for Cheeger cuts, which balance between finding clusters that require cutting few graph edges and finding clusters which are similar in size.

Location: https://www.oneworldml.org/upcoming-events

Machine Learning for Your Research

This workshop will give an overview of several modern supervised and unsupervised machine learning methods. We will discuss the advantages and limitations of each and explore what types of problems each is best suited to address.

Workshop format: Lecture and discussion


CITP Seminar: Tal Zarsky – When Small Change Makes a Big Difference: Algorithmic Equity Among Similarly Situated Individuals

Azure Data Management and Storage

This workshop is an introduction to working with data in the cloud on Azure. You will walk through the different data structures and how they can be managed, consumed, and accessed in Azure. This workshop also explores solutions and integrations with common tools used for extract, transform, and load (ETL) processes. You will leave with an...

Online Optimization & Energy

Online optimization is a powerful framework in machine learning that has seen numerous applications to problems in energy and sustainability. In my group at Caltech, we began by applying online optimization to ‘right-size’ capacity in data centers nearly a decade ago; and by now tools from online optimization have been applied to develop...
Location: Virtual Seminar
Tags: Seminars

Hydrological modeling in the era of big data and artificial intelligence

Nowadays, all sorts of sensors, from ground to space, collect a huge volume of data about the Earth. Recent advances in artificial intelligence (AI) provide unprecedented opportunities for data-driven hydrological modeling using such “Big Earth Data”. However, many critical issues remain to be addressed. For example, there lacks efficient...
Location: Virtual Seminar

Leveraging the Advanced Capabilities of the Traverse Supercomputer

The new Traverse supercomputer, which is composed of 46 IBM POWER9 nodes with 4 NVIDIA V100 GPUs per node, has an impressive peak performance of over 1.4 PFLOPS. However, to take full advantage of this computational power, one must have specialized knowledge of both the hardware and software.

Azure Machine Learning

In this workshop, you will learn the most important concepts of the machine learning workflow that data scientists follow to build an end-to-end data science solution on Azure. You will learn how to find, import, and prepare data, select a machine learning algorithm, train, and test the model, and deploy a complete model to an API. You will get...