Marine Sciences Machine Learning Workshop

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Hands-on experience with Machine Learning tools and techniques applicable in marine biology

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This summer, Simon Fraser University (SFU) is partnering with The Texas Advanced Computing Center (TACC) to offer a Marine Sciences Machine Learning Workshop, focused on applying Machine Learning and Deep Learning tools and techniques to marine biology, in an effort to better analyze and categorize datasets unique to this field.

In this two week workshop, you will learn techniques in supervised and unsupervised learning, as well as the technologies and principles required in scalable computing. During this virtual event, you will:

  • Learn from leading TACC and SFU researchers and scientists
  • Participate in a guided hackathon to immediately apply the topics learned and analyze real world datasets from marine sciences using TACC's wide array of advanced computing resources
  • Gain experience using TACC's Frontera supercomputer.
  • See how machine learning techniques can uncover hidden insights in huge datasets

This course runs August 9 - 20 (10 days, 8:30am to 10:30am and then 12:00pm to 2:00pm PDT each day excluding weekends)

What You'll Learn

Topics covered in this workshop include: Jupyter, Python, Machine Learning using: Unsupervised Learning with Principal Component Analysis, Clustering, Multidimensional Scaling, Supervised Learning using Linear Modeling, Support-Vector Machine, Tree-based Classifiers, and Naive Bayesian Classifiers, as well as Deep Learning techniques on building Neural Networks with Convolutional Neural Networks and Recurrent Neural Networks, and Distributed Learning.

$700 Grant

You may qualify for the $1000 Scale AI grant. You'll be sent a discount code after you apply. This grant cannot be combined with the Athena Pathways scholarship. Apply for the grant

$500 Scholarship

Our partner Athena Pathways is offering a $500 scholarship designed to lower barriers for women pursuing careers in the AI and data science fields. This scholarship will be awarded after completion of the workshop. Any person who identifies as female and resides in British Columbia will qualify. Please contact sfu_bigdata@sfu.ca if you have any questions or visit the scholarship application page for more information. This scholarship cannot be combined with the Scale AI Grant. Apply now


August 9 to August 20, from 8:30am to 10:30am and then 12:00pm to 2:00pm PDT each day (excluding weekends).

Additional pre- and post- workshop training and mentoring will run August 4 (9:00am to 11:00am and then 12:00pm to 2:00pm PDT) and August 24, 2021 (9:00am to 11:00am and then 12:00pm to 2:00pm PDT)

Free Bonus Workshops

By registering through Simon Fraser University, you are automatically enrolled in two additional free one-day workshops, held on the first and fourth week of August.

1) A Gentle Introduction to Principal Component Analysis Workshop

August 4 (9:00am to 11:00am and then 12:00pm to 2:00pm PDT)

The Canadian Statistical Sciences Institute is partnering with SFU to offer a one-day workshop designed to provide researchers with the basic understating of Principal Component Analysis and how (and when) it can be used to work with complex data sets. The course will be taught be Dr. Don Estep, Director of CANSSI, and a Tier 1 Canada Research Chair in the Department of Statistics and Actuarial Science at SFU.

2) Advances in Marine Data Science

August 24 (9:00am to 11:00am and then 12:00pm to 2:00pm PDT)

This one-day interactive workshop highlights the use of data driven techniques to solve some of the most challenging issues affecting marine science practitioners. Participants will be able to interact with researchers concerning issues related to data, techniques and results.

Download Syllabus

Download the Syllabus. For any questions, please contact sfu_bigdata@sfu.ca


SFU Instructors:

Stephen Makonin, Adjunct Professor, School of Engineering Science

Jillian Anderson, Big Data Developer, SFU's Research Computing Group

Steven Bergner, University Research Associate, SFU's Big Data Hub

Don Estep, Scientific Director, The Canadian Statistical Sciences Institute

TACC Instructors:

Charlie Dey, Director , Training And Professional Development

Amit Gupta, Research Engineering/Scientist Associate III, Data Intensive Computing

Kelly Pierce, Research Assistant, Data Mining and Statistics

Je’Aime Powell, Senior Systems Administrator, Data Management & Collections

David Walling, Software Developer, Data Intensive Computing

Weijia Xu, Research Engineer and Manager, Data Mining And Statistics, Data Intensive Computing

Zhao Zhang, Research Associate, Data Mining & Statistics

Guest Speakers

Additional guest speakers will be announced soon.

Christopher Biggs, University of Texas at Austin Marine Science Institute

Marc-Antoine Drouin - Senior Research Officer, National Research Council, Computer Vision and Graphic team

Youlian Pan, Senior Research Officer in Digital Technologies, National Research Council of Canada

Fred Popowich, Scientific Director, SFU's Big Data Hub

Philip Souza, University of Texas at Austin Marine Science Institute

Xuekui Zhang, Assistant Professor & Canada Research Chair (tier 2) in Bioinformatics and Biostatistics at the University of Victoria


Please contact sfu_bigdata@sfu.ca

About TACC

The Texas Advanced Computing Center (TACC) designs and operates some of the world's most powerful computing resources. The center's mission is to enable discoveries that advance science and society through the application of advanced computing technologies.

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About SFU's Big Data Hub

Simon Fraser University leverages the power of big data so Canada can lead in a digital world. With over a decade of leadership in the big data field, SFU’s Big Data Hub engages with our partners to fill critical talent shortages, generate new knowledge and contribute to an innovative economy. We connect government to industry and the community to deliver data-driven solutions to challenging problems. With 24 governmental partners and over 100 companies actively engaged, we are empowering people to use data for impact and social good to solve global challenges and transform society.

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