Theoretical Foundations of Data Science I

LEC 2 Empirical Risk Minimization
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HOPS 0 Linear Algebra Bootcamp (For the Soul)

HOPS 1 How to Prove it! (Look Over Independently)
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SUR Welcome Survey

HW Homework 0 (Not Due!)

LEC 4 Simple Linear Regression
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HOPS 2 Loss Functions & Risk
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HOPS 3 MSE vs MAE vs Huber
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HW Homework 1 Released

LEC 6 Dot Products and Projections
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HOPS 4 Simple OLS Regression
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HOPS 5 Regression & Linear Algebra
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DEMO Simple Linear Regression + Huber Loss

DISC Groupwork 1 (Submit Handwritten, Individually!)
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LEC 8 Regression and Linear Algebra
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HOPS 6 Regression in the Real World
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DEMO Demo 2 - Interaction Terms

HW Homework 2 Released

LEC 10 Feature Engineering, Gradient Descent
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HOPS 7 Feature Engineering + Normal Equations
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HOPS Midterm Review (Online)

DISC Groupwork 2 (Submit Handwritten, Individually!)
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LEC 11 Gradient Descent, Continued
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HOPS 8 Gradient Descent (Look Over Independently)
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DEMO Loss Surface Navigation + Regularization

HW Homework 3 Released

LEC 13 Combinatorics
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HOPS 9 Gradient Descent Again
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HOPS 10 Conditional Probability
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DISC Groupwork 3 (Submit Handwritten, Individually!)
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LEC 15 Bayes' Theorem and Independence
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HOPS 11 Approaching Probability Problems
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HOPS 12 Combinatoric Problems
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DEMO Probability + Real World DS Practices

HW Homework 4 Released

LEC 17 Naïve Bayes
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HOPS 13 Bayes Theorm vs Frequentist
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HOPS 14 Naïve Bayes
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DEMO Demo 6 - Multi-armed Bandit

DISC Groupwork 4 (Submit Handwritten, Individually!)
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LEC 19 Conclusion + Final Exam Review (LIVE)

DEMO Demo K-Means Clustering