re
[Python re
slides]Week | Deliverables (*) | Lecture Hour | Lecture Date | First Slide | Video Link |
---|---|---|---|---|---|
1 | 1 | Sep 9 | Intro | 1-1 (0:50) | |
2 | Exer 1 | 2 | Sep 13 | Getting Data | 2-1 (0:48) |
3 | Sep 13 | Operating on Arrays | 2-2 (0:49) | ||
4 | Sep 16 | exercise time (in-person) | |||
3 | Exer 2 | 5 | Sep 20 | Getting Data | 3-1 (0:48) |
6 | Sep 20 | Noise | 3-2 (0:48) | ||
7 | Sep 23 | exercise time (in-person) | |||
4 | Exer 3 | 8 | Sep 27 | Kalman Parameters | 4-1 (0:48) |
9 | Sep 27 | Entity Resolution | 4-2 (0:48) | ||
10 | Sep 30 | Truth and Reconciliation Day | |||
5 | Exer 4 | 11 | Oct 4 | Specific Distrib | 5-1 (0:47) |
12 | Oct 4 | Transforming Data | 5-2 (0:46) | ||
13 | Oct 7 | exercise time (in-person) | |||
6 | Exer 5 | 14 | Oct 11 | p-hacking | 6-1 (0:49) |
15 | Oct 11 | Machine Learning | 6-2 (0:39) | ||
16 | Oct 14 | exercise time (in-person) | |||
7 | Exer 6 | 17 | Oct 18 | Polynomial Regression | 7-1 (0:47) |
18 | Oct 18 | Naïve Bayes | 7-2 (0:48) | ||
19 | Oct 21 | exercise time (in-person) | |||
8 | Exer 7, Quiz 1 | 20 | Oct 25 | More Than Points | 8-1 (0:48) |
21 | Oct 25 | Random Forests | 8-2 (0:46) | ||
22 | Oct 28 | Quiz 1 | |||
9 | Exer 8 | 23 | Nov 1 | Perceptrons | 9-1 (0:48) |
24 | Nov 1 | Anomaly Detection | 9-2 (0:48) | ||
25 | Nov 4 | exercise time (in-person) | |||
10 | Exer 9 | 26 | Nov 8 | DFs are Partitioned | 10-1 (0:45) |
27 | Nov 8 | How Spark Calculates | 10-2 (0:49) | ||
28 | Nov 11 | Remembrance Day | |||
11 | Exer 10 | 29 | Nov 15 | Execution Plans | 11-1 (0:48) |
30 | Nov 15 | Spark Join | 11-2 (0:47) | ||
31 | Nov 18 | exercise time (in-person) | |||
12 | Exer 11 | 32 | Nov 22 | SQL? | 12-1 (0:50) |
33 | Nov 22 | Big Data is annoying. | 12-2 (0:47) | ||
34 | Nov 25 | exercise time (in-person) | |||
13 | Exer 12, Quiz 2 | 35 | Nov 29 | Pandas Speed: Numexpr | 13-1 (1:00) |
36 | Nov 29 | ||||
37 | Dec 2 | Quiz 2 | |||
14–15 | Project, Final Quiz | 38 | Dec 6 | no lecture | |
39 | Dec 6 |
* Check CourSys for the actual due dates and times.