# CS2810 Homepage

Math of Data Models

Spring 2022

# Schedule & Notes

all google colab python examples

 Idx Day Date Topic HW# (class idx) (due)[max late] Class notes 1 Mon Tue Jan 17*/18 Data Models Intro Linearity Gauss Jordan Elimination `sec1` `sec2` `sec3` 2 Thu Fri Jan 20/21 RREF Vector algebra Solution space of system `sec1` `sec2&3` 3 Mon Tue Jan 24/25 Singular / homogenous matrix Vector Geometry: (length, angle, dot) HW 1 (1-3) (Wed Feb 2)[2] `sec1` `sec2&3` 4 Thu Fri Jan 27/28 Is Machine Learning Good? Linear Perceptron `sec1` `sec2&3` `sec2&3_ica` 5 Mon Tue Jan 31 Feb 1 Linear Perceptron `sec1` `sec2&3` perceptron 6 Thu Fri Feb 3/4 Matrix Multiplication Matrix Transforms HW 2 (4-6) (Sun Feb 13)[1] `sec1` `sec2` `sec3` 7 Mon Tue Feb 7/8 Span Linear Independence `sec1` `sec2` `sec3` 8 Thu Fri Feb 10/11 Projections Line of best fit Polynomial of best fit `sec1` `sec2` `sec3` line_best_fit calc_lin_alg 9 Mon Tue Feb 14/15 Inverses Change of basis HW 3 (7-9) (Sun Feb 21)[1] `sec1` `sec2` `sec3` 10 Thu Fri Feb 17/18 Quiz 1 (HW 1-2) Dynamical system (intro) `sec2` `sec3` 11 Mon Tue Feb 21*/22 Eigenvectors Dynamical system HW 4 (10-11) (Sun Feb 27)[2] sec1_lec_canvas `sec1_lec11.zip` `sec2` `sec3` 12 Thu Fri Feb 24/25 Begin Prob & Stats: Expectation & Variance Linearity of Expectation `sec1` `sec2&3` 13 Mon Tue Feb 28 Mar 1 Independence Law of large numbers Binomial / Poisson Distribution HW 5 (12-13) (Sun Mar 6)[2] `sec1` `python_examples.py` `sec2` `sec3` law_large_num_demo prob_stats_calc 14 Thu Fri Mar 3/4 Quiz 2 (HW 3-4) 15 Mon Tue Mar 7/8 Estimators Bias Bessel’s correction HW 6 (14-15) (Sun Mar 20)[2] `sec1` `sec2` `sec3` sec2&3_bessel 16 Thu Fri Mar 10/11 Mini-Project Day (Line of Best Fit, Perceptron, dynamical system) sec1 sec1_bessel `sec2&3` Break 17 Mon Tue Mar 21/22 Normal distribution Central Limit Theorem Cumulative Distribution Function `sec1` `pdf_cdf_sec1.ipynb` `pdf_cdf_sec1.html` `sec2` `sec3` cdf_sec2&3 central_limit_theorem 18 Thu Fri Mar 24/25 Hypothesis testing P-value HW 7 (17-19) (Sun Apr 3)[2] `sec1` `sec2` `sec3` 19 Mon Tue Mar 28/29 T-tests One vs two sided tests Experimental bias `sec1` `sec2` `sec3` ttest_example_excel `ttest_example.html` `ttest_example.ipynb` 20 Thu Fri Mar 31 Apr 1 Quiz 3 (HW 5-6) 20** Mon Tue Apr 4/5 Chi square test Multiple comparison correction `sec1` `sec2` `sec3` `chisquare_example.html` `chisquare_example.ipynb` 21 Thu Fri Apr 7/8 Covariance Covariance matrix HW 8 (20-22) (Sun Apr 17)[2] `sec3` 22 Mon Tue Apr 11/12 Correlation Independence Bayes Rule `sec1` `sec2` `sec3` 23 Thu Fri Apr 14/15 Bayes Nets 1 `sec1` bayes_example `sec2` `sec3` 24 Mon Tue Apr 18*/19 Bayes Nets 2 HW 9 (22-24) (Weds Apr 27)[2] `sec1` `sec2` `sec3` `joint_ex.csv` 25 Thu Fri Apr 21/22 Mini-Project Day: Hypothesis Testing Bayes Net `sec1` `sec2&3` mini_proj2 26 Mon Tue Apr 25/26 Finals Review sec1 `sec2` `sec3` May 3 “Final” (Sec2&3) Quiz 4 (HW 7-9) Ell Hall AUD (8-10am) May 4 “Final” (Sec1) Quiz 4 (HW 7-9) Snell Engineering Center 108 (1-3pm) May 6 “Final” (sec3 option) Quiz 4 (HW 7-9) Mugar Life Science Building 201 (8-10am)

Note that we’ll take quiz-test 4 during the time slot given by the finals schedule.

*denotes asynchronous lectures given to section 1 (university holiday on that day)

** we lost our index sync from lessons 14 to 20 (pdfs are labelled with a different day than this table) we’re repeating index 20 to get back on track without renaming anything to confuse folks. sorry about that!