Predicting House Prices
Data science project
Project overview
The goal of this Project was to predict the house price, as students it was also to get a first look at data science tools. This is the dataset used in the second chapter of Aurélien Géron's recent book 'Hands-On Machine learning with Scikit-Learn and TensorFlow'. It serves as an excellent introduction to implementing machine learning algorithms because it requires rudimentary data cleaning, has an easily understandable list of variables and sits at an optimal size between being to toyish and too cumbersome.
The data contains information from the 1990 census. It does provide an accessible introductory dataset for teaching people about the basics of machine learning.
Value of the research
During development I had problems when representing linear algebra in the area of matrices and vectors, but during the journey I was applying the concepts. Having a first contact with data science is what I learned from this project, from using tools like tensoflow, tensorboard to better optimization of hyperparameters and using interactive visualisation tools.
Data and Methods
- Outlier treatment
- One Hot encoding
- Feature Scaling
Professors
- Ing. Luis Leal
- Msc. Preng Biba
Screenshots
