Module 2: Wrangle ML Datasets
Module Overview
In this module, you'll learn essential techniques for wrangling datasets for machine learning. Data preparation is a critical step in the machine learning workflow, often taking up to 80% of a data scientist's time. You'll explore methods for data cleaning, exploration, and joining relational data to create meaningful feature sets for your models.
Learning Objectives
- explore tabular data for supervised machine learning
- join relational data for supervised machine learning
Guided Project
Open DS_232_guided_project.ipynb in the GitHub repository below to follow along with the guided project:
Guided Project Video
Module Assignment
For this assignment, you'll continue working with your portfolio dataset from Module 1. You'll apply what you've learned to clean, explore, and prepare your data for modeling.
Note: There is no video for this assignment as you will be working with your own dataset and defining your own machine learning problem.