Neural Networks with PyTorch (Beginners)

Introduction

In this project we will go through some basic data pre-processing with Python, visualize our dataset with Seaborn and Matplotlib, split it with sklearn, and train a simple Multi-Layer Perceptron (MLP) using PyTorch to solve the WIDS22 Challenge prediction problem. The implementation is based on the Kaggle notebook.

Getting Started

We recommend using a python virtual environment

python3 -m venv WIDS python=3.10

Install the requirements

pip3 install -r requirements.txt

Train the model

python train.py

You can visualize the dataset by passing the command -v True and change the epoch number by setting -e <number_of_epochs>.

The training statistics can be found on tensorboard log directory and can be accessed by running:

tensorboard --logdir runs