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Deep Learning

Spring 2024

Feb 2, 2024

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May 3, 2024

Register

You are registered for this program.

Registration Deadlines

Feb 7, 2024

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Erdős members / alumni who have completed a prior Erdős Data Science Project

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Category

Advance, Supplemental, Self-Directed, Mini-Course

Overview

This is a self-paced deep learning boot camp, using the FastAI book as the foundation (http://course.fast.ai). It is suggested you take 12-15 weeks to go through the material. If possible, you should meet with others to have a weekly discussion group on the material.

In order to receive a deep learning certificate, you must submit a (team-based) final project by **May 03, 2024**.

Organizers and Instructors

matt_osborne.png

Lindsay Warrenburg

Lead Instructor

Office Hours:

as needed

Email:

Preferred Contact:

Slack

Participants should feel free to Slack me with any questions or comments!

Objectives

- Learn the basics of deep learning
- Understand how deep learning is used in industry
- Feel comfortable with deep learning code (PyTorch and FastAI)

First Steps/Prerequisites

Participants must have completed the data science bootcamp before taking this course.

First Steps
Slack

Slack Channel: #slack-channel

Program Content

Welcome to the asynchronous deep learning bootcamp! This course is asynchronous, so there are no set meeting times for lectures. The way the course will work is the following: 


  1. You will read through the corresponding fastai chapters (http://github.com/fastai/fastbook) for a particular lesson on your own.

  2. You are encouraged to form your own group to have weekly discussions based on the assigned readings (see the calendar link below). Those meetings will be used to ask each other questions and to spark discussion about applications of deep learning in data science careers. 

  3. You will form teams to create a final deep learning project, which will be **due on May 03, 2024**. You must submit a final project to receive a deep learning certificate. 

Please note that all of the materials in this course are based on the content in Jeremy Howard and Sylvain Gugger's fastai course (http://course.fast.ai) and corresponding fastai book (http://github.com/fastai/fastbook). 


The copyright of the fastai material is: @book{ howard2020deep, title={Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD}, author={Howard, J. and Gugger, S.}, isbn={9781492045526}, url={https://books.google.no/books?id=xd6LxgEACAAJ}, year={2020}, publisher={O'Reilly Media, Incorporated} } 


The notebooks in the Erdős GitHub repo contain summaries I created of the fastai content in order to consolidate the material and serve as a good review.

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Program Content

Textbook/Notes

Orientation

Introduction

Lindsay Warrenburg introduces the structure of this advanced Deep Learning Course.

Transcript
Code

Project/Homework Instructions

You will form teams to create a final deep learning project, which will be **due on May 03, 2024**. You must submit a final project to receive a deep learning certificate.

Project/Team Formation
Project Submission
Projects README

Schedule

Click on any date for more details

Deep Learning Orientation

February 2, 2024 at 5:00:00 PM

EVENT

Aware Corporate Challenge Introduction

March 1, 2024 at 8:00:00 PM

EVENT

Please check your registration email for program schedule and zoom links.

Project/Homework Deadlines

Feb 2, 2024

10:00 PM

Deep Learning Registration Form

This is used to gain access to Slack / Github and to help find teams in similar time zones

Feb 9, 2024

2:34 PM

Deep Learning Group Formation

This is your study group team and your project team

May 3, 2024

9:00 PM

Deep Learning Final Project Due

Click on this box to submit project

To access the program content, you must first create an account and member profile and be logged in.

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