|
|
Class Description
Every technical product is now incorporating machine learning at an explosive rate. But most people, even those with strong technical skills, don't understand how it works, what its capabilities are, and what security risks come with it. In this workshop, we'll make machine learning models using simple Python scripts, train them, and evaluate their value. Projects include computer vision, breaking a CAPTCHA, deblurring images, regression, and classification tasks. We will perform poisoning and evasion attacks on machine learning systems, and implement deep neural rejection to block such attacks.
No experience with programming or machine learning is required, and the only software required is a Web browser. We will use TensorFlow on free Google Colab cloud systems.
Textbooks
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Github
AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence (optional)
Quizzes
The quizzes are multiple-choice, online, and open-book. However, you may not ask other people to help you during the quizzes. You will need to study the textbook chapter
before the lecture covering it, and take the quiz before that class.
Each quiz is due 30 min. before class. Each quiz has 5 questions, you have ten minutes to take it, and you can make two attempts. If you take the quiz twice, the higher score counts.
Canvas is not ready yet.
|
Schedule |
|---|
| Date | Due | Topic |
|---|
|
| Wed 8-19 | |
Machine Learning for N00bs
Demo: ML 130
|
|
| Wed 8-26 | |
1 The Machine Learning Landscape
OWASP Top Ten
Demo: ML 100
|
|
| Wed 9-2 | Quizzes Ch 1 and 2
Proj ML 130 |
2 End-to-End Machine Learning Project
Demo: ML 104 (in the Ch 2 lecture) and 101 and 123
|
|
| Wed 9-9 | Quiz Ch 3
Proj ML 100 |
3 Classification
Demo: ML 102 and 103
|
|
| Wed 9-16 | Quiz Ch 4
Proj ML 101 & ML 102 |
4 Training Models
Demo: ML 105 and 106 and 112
|
|
| Wed 9-23 | Quiz Ch 5
Proj ML 103 & ML 104 |
5 Support Vector Machines
Demo: ML 107 and 108 and Security Risks projects
|
|
| Wed 9-30 | Quiz Ch 6
Proj Ml 105 & ML 106 |
6 Decision Trees
Demo: ML 113 and 109 and 110
|
|
| Wed 10-7 | Quiz Ch 7
Proj Ml 107 & ML 108 |
7 Ensemble Learning and Random Forests
Demo: ML 114 and 111 and 120
|
|
| Wed 10-14 | Quiz Ch 8
Proj Ml 109 & ML 110 |
8 Dimensionailty Reduction
Demo: ML 115 and 121 and 122
|
|
| Wed 10-21 | Quiz Ch 9
Proj ML 111 & ML 120 |
9 Unsupervised Learning Techniques
Demo: ML 116 and 109
|
|
| Wed 10-28 | Quiz Ch 10
Proj Ml 121 & ML 122 |
10 Introduction to Artificial Neural Networks
Demos: ML 126 and 127
|
|
| Wed 11-4 | No Quiz
|
TBA
|
|
| Wed 11-11 | No Quiz |
Holiday: No Class
|
|
| Wed 11-18 | Quiz Ch 11
|
11 Training Deep Neural Networks
|
|
| Wed 11-25 | Quiz Ch 12
|
12 Custom Models and Training with Tensorflow
|
|
| Wed 12-2 | No Quiz
|
TBA
|
|
| Wed 12-9 | No Quiz
|
Last Class: TBA
|
|
Tue 12-15
through
Tue 12-22 | |
Final Exam available online throughout the week.
You can only take it once. |
|
| All quizzes due 30 min. before class
|
