This course will introduce students to the exciting and rapidly evolving field of artificial intelligence and machine learning. Upon completion of this course, students will understand key concepts that are fundamental to machine learning and deep learning in particular. The course will involve lectures and short programming assignments on the fundamentals of data management, classification, regression, and neural networks. Applications of deep learning to self-driving cars, medical imaging, and more will also be presented. Students will be asked to read and present a research paper as the final project.

Syllabus Please check this syllabus link for the latest version of the lecture schedule.

Lectures

Title Date Instructor Materials
Introduction to ML and AI 2018-06-14 Scott Siegel [Slides]
Fundamentals of supervised learning 2018-06-19 Patrick Emami [Notebook]
Intro to programming for data science 2018-06-21 Patrick Emami [Notebook] [Completed Notebook] [Data]
Template Matching for Object Detection 2018-06-26 Pan He [Slides]
Object Recognition and Detection: An Overview before the Age of Deep Learning 2018-06-28 Pan He [Slides]
Neural Networks Part I 2018-07-03 Patrick Emami [Slides][Lecture notes]
Neural Networks Part II 2018-07-10 Pan He [Slides]
Intro to Convolutional Neural Networks 2018-07-12 Scott Siegel [Notebook] [Slides]
Best Practices in Deep Learning 2018-07-17 Scott Siegel [Slides]

Working with Colab notebooks

After opening a Colab notebook, click “open in playground” to edit the cells. To run a cell containing code, click the “run” button by the cell. It will prompt you to sign-in with a Google account. Once you do this, you can run the code for yourself. To save any changes to the notebook, you must click “copy to drive”.

Programming Assignments

Assignment Due date Materials
Homework 1 2018-06-26 11:59 PM Notebook
Homework 2 2018-07-05 (New deadline) 11:59 PM Notebook
Homework 3 2018-07-24 11:59 PM Notebook

Submission instructions

Please open and edit the notebook directly, following the instructions above for Colab notebooks. When you finish, click “File” -> “Download .ipynb”. For Homework 1, email the file to pemami at ufl dot edu or pan dot he at ufl dot edu (replace at with @ and dot with .). For Homework 2, email the file to pan at ufl dot edu.

Supplementary material