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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 mini_proj1 mini_proj1_csv
		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]	sec1 cov_corr_example.html cov_corr_example.ipynb sec2 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!