Importing data sets and finding statistics

Slicing and indexing data sets

What types of problems and models exist in machine learning? What do most models have in common?

Linear Regression and Feature Importance

Types of regression models and what each one is typically used for.

How does gradient descent work, and how can we use it to optimize our models?

Logistic regression

Decision trees and feature importance

More on decision trees and using ensemble methods to improve performance

Clustering models and unsupervised learning

Train test split AUC score, accuracy / precision / recall

Finding/starting a project

Finding and starting a project

Related Works + Experiment Design

Results

Writing, and related works

Writing, Introduction and Abstract

Finishing the Research Project