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.
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.
Don't use CCSF's Canvas system for this class. Instead, all students
should use this Canvas server:
Machine Learning for N00bs
1 The Machine Learning Landscape
OWASP Top Ten
Demo: ML 130
Fri 1-31
Quizzes Ch 1 and 2 Proj ML 130
2 End-to-End Machine Learning Project
Demo: ML 100, ML 104, ML 123
Fri 2-7
Quiz Ch 3 Proj ML 100
3 Classification
Demo: ML 105
Fri 2-14
No Quiz
Class Cancelled for CactusCon
Fri 2-21
Quiz Ch 4 Proj ML 101 & ML 102
4 Training Models
Demo: ML 101, 102, 103
Fri 2-28
Quiz Ch 5 Proj Ml 103 & ML 104
5 Support Vector Machines
Demo: ML 112
Fri 3-7
Quiz Ch 6 Proj Ml 105 & ML 106
6 Decision Trees
Demo: ML 113
Fri 3-14
Quiz Ch 7 Proj Ml 107 & ML 108
7 Ensemble Learning and Random Forests
Demo: ML 114
Fri 3-21
Quiz Ch 8 Proj Ml 109 & ML 110
8 Dimensionailty Reduction
Demo: ML 115 and ML 109
Fri 3-28
Quiz Ch 9 Proj Ml 111 & ML 120
9 Unsupervised Learning Techniques
Demo: ML 116
Fri 4-1
No Quiz
No Class: Spring Break
Fri 4-11
Quiz Ch 10 Proj Ml 121 & ML 122
10 Introduction to Artificial Neural Networks
Fri 4-18
Quiz Ch 11
11 Training Deep Neural Networks
Fri 4-25
Quiz Ch 12
12 Custom Models and Training with Tensorflow
Fri 5-2
No Quiz
TBA
Fri 5-9
No Quiz
Last Class: TBA
Wed 5-14 through Wed 5-21
Final Exam available online throughout the week.
You can only take it once.
All Quizzes due 30 min. before class
Lectures
The Fundamentals of Machine Learning
Machine Learning for N00bs
KEY ·
PDF
1 The Machine Learning Landscape
KEY ·
PDF
OWASP Top 10 Machine Learning Security Risks ·
KEY ·
PDF OWASP Top 10 for LLM (PDF)
2 End-to-End Machine Learning Project
KEY ·
PDF
3 Classification
KEY ·
PDF
4 Training Models
KEY ·
PDF
5 Support Vector Machines
KEY ·
PDF
6 Decision Trees
KEY ·
PDF
7 Ensemble Learning and Random Forests
KEY ·
PDF
8 Dimensionailty Reduction
KEY ·
PDF
9 Unsupervised Learning Techniques
KEY ·
PDF
Neural Networks and Deep Learning
10 Introduction to Artificial Neural Networks
KEY ·
PDF
11 Training Deep Neural Networks
KEY ·
PDF
12 Custom Models and Training with Tensorflow
KEY ·
PDF
13 Loading and Preprocessing Data with Tensorflow
KEY ·
PDF
14 Deep Computer Vision Using Convolutional Neural Networks
15 Processing Sequences Using RNNs and CNNs
16 Natural Language Processing with RNNs and Attention
