Build a predictive model for Otto Group Product Classification

Build a predictive model for Otto Group Product Classification

Build a predictive model to correctly classify products between 9 product categories (fashion, electronics, etc.) using the Otto Group dataset.

Videos

Each project comes with 2-5 hours of micro-videos explaining the solution.

Code & Dataset

Get access to 50+ solved projects with iPython notebooks and datasets.

Project Experience

Add project experience to your Linkedin/Github profiles.

Customer Love

Read All Reviews

Hiren Ahir

Microsoft Azure SQL Sever Developer, BI Developer

I'm a Graduate student and came into the job market and found a university degree wasn't sufficient to get a good paying job. I aimed at hottest technology in the market Big Data but the word BigData... Read More

Mohamed Yusef Ahmed

Software Developer at Taske

Recently I became interested in Hadoop as I think its a great platform for storing and analyzing large structured and unstructured data sets. The experts did a great job not only explaining the... Read More

What will you learn

Understanding the problem statement and importing the file
Initializing the libraries and understand it's use
Check for null values and necessary imputations
Use and interpret the summary function in R
Use a Box plot to identify the outliers and handle them
Applying ensembling model Decision Tree for a Multi-Class Classification problem
Preparing the dataset and training the model
Parameter tuning for better results
How to use Confusion Matrix for a Multi-Class Classification problem
Making final predictions from the trained model

Project Description

The dataset has 93 features for more than 200,000 products with the Test Data containing 144K rows and Training Data containing 61K rows. This data science project is a supervised , multinomial classification problem. The dataset has a total of 9 possible product lines and the objective is accurately make class predictions on 144,000 unlabeled products based on the 93 features for the products provided in the dataset.

Similar Projects

Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

In this data science project, we will predict internal failures of Bosch using thousands of measurements and tests made for each component along the assembly line.

In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.

Curriculum For This Mini Project

19-Mar-2016
03h 58m