Description The project includes the three sprints of the module. The aim is to develop a predictive model based on regression to calculate the price of a house according to the different variables of the dataset, choosing the model that best fits according to the analyzed metrics. At least 3 hypothetical scenarios should be carried out in order to compare them and point out the most optimal scenario.
For the project, we will use the following public dataset found in Kaggle:
https://www.kaggle.com/shree1992/housedata
Project phases:
Phase 1: Import of the dataset Phase 2: Exploratory data analysis Phase 3: Training phase Phase 4: Evaluation and analysis of results Optional part:
Additional phase (optional): investigate the different clouds seen during class 3 and import the project into one of the clouds.