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