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

1. Clone this project on your local repository

git clone <repository link>

2. Install virtual environment in your system

pip3 install virtualenv

3. Create virtual environment

virtualenv env

4. Activate your virtual environment

source env/bin/activate

5. Install the required packages

pip3 install flask, numpy, nltk, matplotlib, pandas, scikit-learn

6. 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