The Otto Group is one of the world's biggest e-commerce companies, with branches in more than 20 countries. The group sells millions of products worldwide every day, with several thousand products being added to their product line. Due to its diverse global infrastructure, many identical products get classified differently.

We will train a machine learning model from the Otto Group dataset which has 93 features for more than 200,000 products. The objective is to build a predictive model which is able to distinguish between our main product categories.

Dataset Link: https://www.kaggle.com/c/otto-group-product-classification-challenge

Project Outline:

Download the dataset.
Explore and analyze the dataset.
Prepare the dataset for ML training.
Train hardcoded and baseline models.
Feature Engineering.
Train and Evaluate different models.
Train Hyperparameters.
Conclusion and References.