This repository contains teaching materials, namely slides and accompanying Jupyter Notebooks corresponding to the weekend lecture sessions I deliver at University of Arizona's Masters in Data Science Program in association with upGrad.
Topics covered so far include
- Time Series Forecasting
- Introduction
- Naive Models
- ARIMA Models
- Exponential Smoothing Models
- Regression Models
- Hands on Session
- Clustering
- KMeans
- KModes
- Hierarchical
- DBSCAN
- Hands on Session
- Model and Feature Selection
- Complexity vs Interpretability
- Bias Variance Tradeoff
- Cross Validation
- Feature Selection
- Regularization
- CTR Prediction Problem Overview
- Kaggle link to the problem statement
- Outline of steps to follow to solve an inbalanced classification problem
- Hands on Session
- Hiring Manager Session
- Interview Questions on the previous topics
- Google Jamboard Scribbles
- Interview Questions