Daily Schedule Part 2 (Actual — Kept Retrospectively)

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See also Daily Schedule - Part 1

Part 2: Data Science Foundations (using Joel Grus, Data Science from Scratch, 2nd Edition)

Part 2 Uses Grus and lasts for the remaining four weeks of Term 6

Week 4 — Yet Another Review of Python — Some Vector and Matrix Algebra — Statistics and Probability

Week 5 — Optimization (aka Minimization and Maximization) — Working with Data

Week 6 — Machine Learning — Linear Regression

In the interest of getting to Neural Networks and Deep Learning in our final week, we are skipping Chapter 12 (on k-Nearest Neighbors), Chapter 16 (on Logistic Regression), and Chapter 17 (on Decision Trees)

Week 7 — Neural Networks — Deep Learning

See also Looking Beyond