AI-First Engineering Cybertraining Spring 2021
5 minute read
This describes weekly meeting and overall videos and homeworks
Contents
Week 1
Lecture
Our first meeting is 01:10P-02:25P on Tuesday
The zoom will be https://iu.zoom.us/my/gc.fox
We will discuss how to interact with us. We can adjust the course somewhat.
Also as lectures are/will be put on YouTube, we will go to one lecture per week – we will choose day
The Syllabus has a general course description
Please communicate initially by email gcf@iu.edu
This first class discussed structure of class and agreed to have a section on deep learning technology.
We gave Introductory Lecture
Assignments
- Assignment Github: Get a github.com account
- Assignment Slack: Enroll in our slack at * https://join.slack.com/t/cybertraining-3bz7942/shared_invite/zt-kzs969ea-x35oX9wdjspX7NmkpSfUpw Post your github account name into the slack channel #general and #ai
- Post a 2-3 paragraph formal Bio (see IEEE papers what a formal bio is. Use google to find examples for Bios or look at Geoffreys or Gregors Web Pages.)
Week 2
Introduction
We gave an introductory lecture to optimization and deep learning. Unfortunately we didn’t record the zoom serssion but we did make an offline recording with slides IntroDLOpt: Introduction to Deep Learning and Optimization and YouTube
Google Colab
We also went through material on using Google Colab with examples. This is a lecture plus four Python notebooks
- First DL: Deep Learning MNIST Example Spring 2021
- Welcome To Colaboratory
- Google Colab: A gentle introduction to Google Colab for Programming
- Python Warm Up
- MNIST Classification on Google Colab
with recorded video
First DL: Deep Learning MNIST Example Spring 2021
We now have recorded all the introductory deep learning material
- slides IntroDLOpt: Introduction to Deep Learning and Optimization
- slides Opt: Overview of Optimization
- slides DLBasic: Deep Learning - Some examples
- slides DLBasic: Components of Deep Learning
- slides DLBasic: Types of Deep Learning Networks: Summary
with recorded videos
IntroDLOpt: Introduction to Deep Learning and Optimization
- Video: IntroDLOpt: Introduction to Deep Learning and Optimization
Opt: Overview of Optimization Spring2021
- Video: Opt: Overview of Optimization Spring2021
DLBasic: Deep Learning - Some examples Spring 2021
- Video: DLBasic: Deep Learning - Some examples Spring 2021
DLBasic: Components of Deep Learning Systems
- Video: DLBasic: Components of Deep Learning Systems
DLBasic: Summary of Types of Deep Learning Systems
- Video: DLBasic: Summary of Types of Deep Learning Systems
Week 3
Deep Learning Examples, 1
We discussed deep learning examples covering first half of slides DLBasic: Deep Learning - Some examples with recorded video
Week 4
Deep Learning Examples, 2 plus Components
We concluded deep learning examples and covered components with slides Deep Learning: More Examples and Components with recorded video
Week 5
Deep Learning Networks plus Overview of Optimization
We covered two topics in this weeks video
- Deep Learning Networks with presentation DLBasic: Types of Deep Learning Networks: Summary
- General Issues in Optimization with presentation Week5 Presentation on Optimization
with recorded video
Week 6
Deep Learning and AI Examples in Health and Medicine
We went about 2/3rds of way through presentation AI First Scenarios: Health and Medicine
with recorded video
Week 7
Deep Learning and AI Examples
- We finished the last 1/3rd of the presentation AI First Scenarios: Health and Medicine
- We finished AI First Scenarios - Space
- We started AI First Scenarios - Energy
with recorded video
Week 8
Deep Learning and AI Examples
- We finished AI First Scenarios - Energy
- We started AI First Scenarios: Banking and FinTech
with recorded video
Week 9
Deep Learning and AI Examples
- We ended AI First Scenarios: Banking and FinTech
- We started AI Scenarios in Mobility and Transportation Systems
with recorded video
Week 10
GitHub for the Class project
- We explain how to use GitHub for the class project. A video is available on YouTube. Please note that we only uploaded the relevant portion. The other half of the lecture went into individual comments for each student which we have not published. The comments are included in the GitHub repository.
Note project guidelines are given here
Video
Week 11
The Final Project
- We described the gidelines of final projects in Slides
- We were impressed by the seven student presentations describing their chosen project and approach.
Video
Week 12
Practical Issues in Deep Learning for Earthquakes
We used our research on Earthquake forecasting, to illustrate deep learning for Time Series with slides
Video
Week 13
Practical Issues in Deep Learning for Earthquakes
We continued discussion that illustrated deep learning for Time Series with the same slides as last week
Video