lecture slides

Below are the links to all slides covered in class. Slides will be posted as soon as they are available.

Lecture #	Date	Topic
1	23 January	Introduction to Data Science
2	28 January	ER Diagrams + Intro to SQL
3	30 January	More SQL, Optimization
4	4 February	Webscraping Slides Class Code
5	6 February	Data Cleaning
6	11 February	Crowdsourcing
7	13 February	Map Reduce
8	20 February	Hypotheses and Hypothesis Testing Intro
9	25 February	Hypothesis Testing: pvalues, t-tests, chi-squared
10	27 February	Hypothesis Testing: Linear Regression
11	3 March	Linear Regression Continued; p-Hacking Class Code
12	5 March	Nonparametric Methods; Bootstrapping Class Code
13	10 March	Introduction to Machine Learning Class Code
14	12 March	Supervised vs. Unsupervised Learning; Clustering
15	17 March	Matrix Factorization + Recommendation Systems Class Code
16	19 March	Classification Class Code
17	31 March	Overfitting, Regularization, and Feature Selection Class Code
18	2 April	Data Visualization Class Code
19	7 April	Natural Language Processing Class Code (NLP Parts 1 and 2)
20	9 April	Natural Language Processing Cont.
21	14 April	Deep Learning
22	16 April	ML Fairness
23	21 April	Time Series (?)
24	23 April	Graphical Models/Causal Inference (?)