Bip xTech: Hands-on Challenge

Credits

Team Aspromonte

• Claudia Chianella (@clauchian)
• Yannick Giovanakis (@yangvnks)
• Flavio Primo (@flaprimo)
• Francesco Zinnari (@FrancescoZinnari)

Method

Below are provided the steps that were followed for this project. Each step and classifiers have their own document.

1. Load Dataframes: load the csv data into Pandas Dataframes and save it for quick use later
2. Data visualization: data analysis to understand missing values, data relations and usefulness of features
3. Preprocessing: with the knowledge acquired with the preceding step, apply preprocessing of data including dealing with missing values and build new features
4. Ensemble: build the model to predict NumberOfSales on test set

Folder structures

• \ contains all of the jupyter's notebooks including models, preprocessing and data visualization
• \Data\input contains the original dataset provided by Bip.
• \Data\output to save the outputs given by intermediate steps (load-dataframes, preprocessing) as well as the final prediction given by the model for the test set (submission.csv

Instructions

Installation instructions

1. Install Python and clone this repository
2. Install required Python modules with pip install -r requirements.txt

to run the jupyter's notebooks just go with jupyter notebook

Run instructions

To run the notebooks follow these steps:

1. Execute load-dataframes notebook
2. Execute data-visualization notebook
3. Execute preprocessing notebook
4. Execute Ensemble notebook

Warning

Intermediate results obtained by the various notebooks were not saved in the current repository. If you want to try the code you have to execute it from the beginning!