Recommender Systems with Machine Learning - Data Preparation for Content-Based Filtering

The video tutorial covers the basics of content-based recommendation systems in Python, focusing on data analysis steps. It begins with an introduction to the concept, followed by importing necessary libraries like pandas, numpy, and matplotlib. The tutorial then explains how to read a CSV dataset and explore its structure, including checking for missing values using pandas functions. The video aims to equip viewers with the skills to handle and analyze movie datasets effectively.

How can you check for missing values in the dataset?

What does a sum of zero in the missing values check indicate?

What is the next step after ensuring there are no missing values in the dataset?