bogdanmagometa / regression-on-tabular-data

Regression on the tabular data

Project structure

• analysis.ipynb - Jupyter notebook with analysis
• modeling.py - Python module that trains the regression on the train data and predicts on the test features
• predictions.csv - file with model predictions for internship_hidden_test.csv (produced by modeling.py)
• README.md
• requirements.txt - Python libraries for installing with pip

Prerequisites

• You need to have conda installed

Environment Setup

Run the following in the project root directory to setup the conda environment:

$ conda create -n reg_on_tab_data python=3.9    # create new virtual env
$ conda activate reg_on_tab_data                # activate environment in terminal
$ conda install jupyter                         # install jupyter + notebook
$ pip install -r requirements.txt               # install python libraries used in analysis.ipynb and modeling.py

Usage

In order to train the model on internship_train.csv and write the predictions for internship_hidden_test.csv into predictions.csv, run the following in the project root directory:

$ python3 modeling.py

Run the following in the project root directory to start jupyter notebook server, then open the analysis.ipynb

$ jupyter notebook