This project aims is explore the principal ideas behind of scikit-learn library. The notebook contain some simple example code to show how scikit-learn work, then we use a real dataset of Montevideo housing prices to create a real model to predict the price of each house.
This project was developed to be shared in Montevideo Applied Data Science, AI and Big Data MeetUp
If you can only look at notebook without run the code. Try here
MyBinder is a free service to run a repository with notebooks in a live sesion without install anything, just click here.
Warning: MyBinder run a temporal sesion, when you leave sesion all your changes are going to be delete.
Colab is a google service to run notebook, but you can only run 1 notebook and to access to complete resources of the repository you should clone repository manually.
Click here to run in colab.
When the sesion are ready run in a new cell the following commnads:
!git clone https://github.com/creyesp/Meetup_uy.git
!mv Meetup_uy/* .
Finally change all path to the current location, for example '../data/ready/properties.csv' to 'data/ready/properties.csv'
If you can save you changes you can save the notebook in your drive.
Install python 3.5+ in your own machine and clone this repository following next step:
$ git clone https://github.com/creyesp/Meetup_uy.git
$ cd Meetup_uy
$ virtualenv --python=python3.6 venv
$ source venv/bin/activate
$ python3 -m pip install --user --upgrade -r binder/requirements.txt
$ jupyter notebook