Before Class¶
\nThe following materials will be covered during the class session.\n
Week |
Session |
Date |
Content |
|---|---|---|---|
1 |
1 |
08/31 |
Please review the syllabus to ensure you have an understanding of expectations for the class. |
1 |
1 |
08/31 |
Please take this short initial survey that will help me in delivering a good class. Link |
1 |
1 |
08/31 |
Join this Webex Teams space. Link |
1 |
2 |
09/03 |
Chapter 1: The Machine Learning Landscape Link |
2 |
3 |
09/08 |
The Hitchhikers Guide to Python - Code Style Link |
2 |
3 |
09/08 |
The Hitchhikers Guide to Python - Code Style Link |
2 |
3 |
09/08 |
Getting Started with Python Environments Link |
3 |
5 |
09/14 |
Chapter 2: End to End Machine Learning Project Link |
3 |
5 |
09/14 |
What is an API? Link |
3 |
5 |
09/14 |
What is an API Economy? Link |
3 |
5 |
09/14 |
Revew the documentation of Twitter API for the end point get User Timelines. Link |
3 |
5 |
09/14 |
Building a web scraper Link |
3 |
5 |
09/14 |
10 Best Visualization Examples Link |
3 |
5 |
09/14 |
Regex Cheatsheet Link |
4 |
8 |
09/24 |
Under and Overfitting in Machine Learning Link |
5 |
9 |
09/28 |
Chapter 3: Classifiication Link |
5 |
10 |
10/01 |
R for Data Science (Skim through book and understand it is available as a reference if needed.) Link |
5 |
10 |
10/01 |
RStudio Cloud Link |
6 |
12 |
10/08 |
Chapter 4: Training Models Link |
8 |
14 |
10/19 |
Chapter 8: Dimensionality Reduction; Chapter 9 Unsupervised Machine Learning Link |
9 |
16 |
10/26 |
Chapter 6: Decision Trees Link |
9 |
17 |
10/29 |
Chapter 7: Ensembe Learning and Random Forrests Link |
11 |
21 |
11/12 |
Chapter 11: Training Deep Neural Networks Link |
12 |
22 |
11/16 |
Chapter 10: Introduction to Artifical Neural Networks with Keras Link |
12 |
22 |
11/16 |
Chapter 12: Custom Models and Training with Tensorflow Link |