Skip to content

hmattie/BST261-Spring2019

Repository files navigation

Welcome to BST261: Data Science II

Deep learning is a subfield of machine learning that builds predictive models using large artificial neural networks. Deep learning has revolutionized the fields of computer vision, automatic speech recognition, natural language processing, and numerous areas of computational biology. In this class, we will introduce the basic concepts of deep neural networks and GPU computing, discuss basic neural networks, convolutional neural networks and recurrent neural networks structures, and examine biomedical applications. Students are expected to be familiar with linear algebra and machine learning and will participate in a group deep learning project.

All course material will be posted here. See below for assignment deadlines.

Course Instructor

Heather Mattie
Instructor of Data Science
Harvard T.H. Chan School of Public Health
Building 1 Room 421A, 655 Huntington Ave, Boston
[email protected]
Office Hour: Wednesdays 1-3pm or by appointment

Course Teaching Assistants

Matt Ploenzke
PhD Candidate, Biostatistics
[email protected]
Office Hour: Fridays 11:15-12:15pm, Kresge 202A, except 3/29 and 5/17
Labs: Fridays 9:45-11:15am, LL6, except 3/29 and 5/17

Aaron Sonabend
PhD Candidate, Biostatistics
[email protected]
Office Hour: Thursdays 1-2pm, Heather's Office

Homework 1: Due Friday, April 12th by 11:59pm

Homework 2: Due Monday, April 29th by 11:59pm

Homework 3: Due Friday, May 10th by 11:59pm

Group Project Proposal: Due Wednesday, May 15th by 11:59pm

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published