Schedule for Section A1

Suggested Readings and Slides:

• Course Overview
• Git Slides

Suggested Readings and Slides:

• Pandas Slides
• Scikit-Learn Slides

Suggested Reading:

• Section A1 pitch slides

Suggested Readings:

• Probability Slides
• Linear Algebra Slides

Suggested Readings:

• Distances and Time Series

Suggested Readings:

• k-means clustering

Suggested Readings:

• Clustering in Practice

Suggested Readings:

• Hierarchical Clustering

Suggested Readings:

• GMM Slides

Suggested Readings:

• Decision Trees and Random Forests

Suggested Readings:

• Classification – kNN

Suggested Readings:

• SVD – Low Rank Approximation

Suggested Readings:

• Dimensionality Reduction and PCA

Suggested Readings:

• Linear Regression

Suggested Readings:

• Logistic Regression
• Regularization

Suggested Readings:

• Neural Networks I

Suggested Readings:

• Neural Networks II

Suggested Readings:

• Neural Networks III

Suggested Readings:

• Networks I

Suggested Readings:

• Networks II

Suggested Readings:

• Recommender Systems – Course Notes

Suggested Readings:

• Time Series Analysis – Course Notes

Suggested Readings:

• Recurrent Neural Networks – Course Notes

Suggested Readings:

• Natural Language Processing – Course Notes

Presentation order TBD.

Presentation order TBD.