This project calculates similarities between 2 text inputs and returns a similarity score between 0 & 1. Developed using NLP Techniques and deployed using Flask. We would use spaCy's en_core_web_lg pipeline for calculating the similarity between texts.

Approach :

• This Notebook focuses on calculating the similarity between 2 texts.
• We will be using a CSV file comprising of 2 independent features, viz. text1 & text2.
• Since there's no dependent variable, we have 2 options : Either treat the problem statement as an unsupervised problem and make clusters, or perform some feature engineering and treat the probem as a regression problem in supervised learning.
• We would go with the supervised learning approach.
• We would use spaCy's en_core_web_lg pipeline for calculating the similarity between texts.
• Please go through Text Similarity.ipynb for the approach in Data Analysis, Feature Engineering and Model Selection, Training, Deployment & Evaluation.
• The app.py flask application is created to to be deployed in a developed environment, which renders the index.html template.
• The index.html page takes 2 text inputs and provides us with the similarity score between 0 & 1 on submitting.
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