Theoretical Foundations of Data Science
DSC 40A, Summer 2023 at UC San Diego
Rod Albuyeh
Instructor
ralbuyeh@ucsd.edu
Lecture: M/W 8:00am-10:50am; RWAC 0115
Office Hours: See Calendar tab; Zoom
Click the 📺 icons below to view lecture recording, and ✏️ for annotated notes.
Week 1
- Mon Jul 3
MOD 1 Learning from Data ✏️ 📺
MOD 2 Minimizing Mean Absolute Error ✏️
MOD 3 Mean Squared Error and Empirical Risk Minimization ✏️
- Tue Jul 4
HW 1 Homework 1
- Wed Jul 5
MOD 4 Center and Spread, Other Loss Functions ✏️ 📺
MOD 5 Gradient Descent ✏️
MOD 6 Gradient Descent in Action ✏️
- Fri Jul 7
GW 1 Groupwork 1 📺
Week 2
- Mon Jul 10
MOD 7 Linear Prediction Rules ✏️ 📺
MOD 8 Simple Linear Regression ✏️
- Tue Jul 11
HW 2 Homework 2
- Wed Jul 12
MOD 10 Regression Via Linear Algebra ✏️ 📺
MOD 11 The Normal Equations ✏️
MOD 12 Multiple Linear Regression and Feature Engineering ✏️
- Fri Jul 14
GW 2 Groupwork 2 📺
Week 3
- Mon Jul 17
MOD 13 Feature Engineering, Clustering ✏️ 📺
MOD 14 Clustering ✏️
PRAC Practice Exam
- Wed Jul 19
EXAM Midterm
- Fri Jul 21
DISC Special Topics: Logistic Regression and Regularization 📺
Week 4
- Mon Jul 24
MOD 15 Foundations of Probability ✏️ 📺
MOD 16 Conditional Probability, Sequences, and Permutations ✏️
- Tue Jul 25
HW 3 Homework 3
- Wed Jul 26
MOD 18 Probability and Combinatorics Examples ✏️ 📺
MOD 19 More Probability and Combinatorics Examples ✏️
- Fri Jul 28
GW 3 Groupwork 3
Week 5
- Mon Jul 31
MOD 21 Independence ✏️ 📺
MOD 22 Independence and Conditional Independence ✏️
MOD 23 Naive Bayes ✏️
- Wed Aug 2
MOD 24 More Naive Bayes ✏️ 📺
MOD 25 Precision and Recall ✏️
MOD 26 Summary and Conclusion ✏️