The goal of the project is to classify product title in an appropriate category which can assist e-commerece sellers in listing products categories.
Product title classication is merely an instance of text classication problems, which are well-studied
in literature. However, product titles possess some properties very different from general
documents. A title is usually a very short description, and an incomplete sentence. A product title
classier may need to be designed differently from a text classier.
We will do exploratory data analysis on the dataset to remove noisy data, then we will perform
feature selection and extraction to identify suitable algorithms for multi-class classification. The
observations and results will be put into production to make it available for the end-users.
NOTE: You must have python pre-installed in your system
- Clone this project on your local repository
git clone <repository link>
- Install virtual environment in your system
pip3 install virtualenv
- Create virtual environment
virtualenv env
- Activate your virtual environment
source env/bin/activate
- Install the required packages
pip3 install flask, numpy, nltk, matplotlib, pandas, scikit-learn
- Execute the following command to run the program
python3 app.py
- Python
- Flask
- NLTK
- HTML
- CSS
- Bootstrap
- Support Vector Machine (SVM)
- Random Forest Classifier
- Jupyter Notebook
- Visual Studio Code