Document Classification using NLP, Machine Learning

Objective

Perform document classification into four defined categories (World, Sports, Business, Sci/Tech). Compare the classifier accuracy with different models ranging from Naïve Bayes to Convolutional Neural Network (CNN) and RCNN. By making use of different feature engineering techniques and extra Natural Language Processing (NLP) features create an accurate text classifier.

Tech Stack

• Language- Python
• Libraries- Pandas, Numpy, Matplotlib, Scikit Learn, Keras, TensorFlow backend
• Models- Naive Bayes, Logistic Regression, Random Forest, XGBoost, Shallow Neural Network, Convulational Neural Network, RCNN

Implementation

Open document_classifier.ipynb in Jupyter to go to the implementation details

The jupyter file also demonstrates loading and using the model for real-time predictions