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Document Search Engine project with TF-IDF abd Google universal sentence encoder model
Tunable full text search engine in JavaScript that: (1) works natively on web apps like Express.js; (2) easy to customize (via BM25) to specific types of documents (e.g. tweets, scientifc journals); (3) is deployable on either the client-side or the server side.
Web app to match resume to job type, using nlp svm classifier model. Data via webscraping. Uploaded resume converted from PDF to text using OCR.
Implementation of a Vector Space Retrieval Model using TF-IDF and cosine similarity on the Cranfield document corpus
This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en
Code for UCSD CSE 258 Web Mining and Recommender Systems
E-Commerce Recommendation System
An NLP model to detect fake news and accurately classify a piece of news as REAL or FAKE trained on dataset provided by Kaggle.
Web search engine to retrieve most relevant web-pages for user search query from web-pages crawled on the UIC domain
Extractive Text Summarizer, based on tf-idf text representation (an example)
Twitter Sentiment Analysis
The project utilizes the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm. The main objective of this project is to measure the similarity between text documents using the TF-IDF algorithm.
Text classification using Naive Bayes Algorithm¶
Checkout my adventures into NLP here.
User-Driven Product Analysis with Web Scraping & Multi-modal NLP: Sentiment Analysis, Feature Extraction, and Recommendation using Amazon Reviews
Elm implementation of Term Frequency-Inverse Document Frequency (TF-IDF) for text analysis
Recommendation systems for Yelp (collaborative filtering & content-based)
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