The assignment content is about building a bike sharing system that can count the number of bikes on rent hourly and daily, using regression models like Decision Tree, Gradient Boosted Tree, and Linear Regression. The goal is to predict the count of bikes on rent based on various parameters. The pre-processing steps include data cleaning, removing irrelevant features, handling null values, and splitting the dataset into training and test sets. The model will be trained and tested using random forest regressor and other algorithms.