This project analyzed and classified French tweets related to climate change and drought using NLP and Machine Learning.

Search anything, instantly

Assessing the impact of different pre-processing techniques for classifying the sentiment of movie reviews

NLP use cases using popular solutions: Frequency Embeddings, Word embedding (word2vec, doc2vec, Glove), RNN,LSTM, Transformers-BERT, Sentence_Transformers etc. PyTorch

An internet search engine written mostly in python. Currently TF-IDF based.

An NLP project to cluster YouTube comments on the basis of their similarity of words

NLP toolkit for those nonsensical ontologies

🔍 Work Wiz 🌟 Work Wiz is a job search platform that matches users with jobs based on their unique skillsets and desired pay, supporting both full-time and freelance opportunities. Using advanced technologies like TF-IDF, cosine similarity, and SVD from Sklearn, we ensure highly relevant search results.

Cereja is a bundle of useful functions we don't want to rewrite and .. just pure fun!

Towards evaluation of fairness in MDD models: Automatic analysis of symptom differences for gender groups in the D-vlog dataset

This repository contains the three projects completed as part of a data structures and algorithms course.

Language-Detection

Utilizing advanced NLP techniques, our project analyzes and summarizes Indian cricket players' Wikipedia content using transformer models and Word2Vec embeddings. Evaluate summaries with ROUGE scores. Enhance decision-making and knowledge extraction with efficient text analysis

Unlock personalized content recommendations on Netflix with my cutting-edge ML project. Say goodbye to aimless scrolling and elevate your binge-watching experience with our user-centric content-based recommender system.

An Autogen-based Multi-LLM System capable of answering research related questions on ACL 2023 Articles to identify gaps and limitations

This script enhances data integration by fuzzy matching company names across datasets using text preprocessing and efficient search algorithms, ideal for reconciling customer and financial data.

Using a modified TF-IDF approach based on Flynn and Sastry's "Attention Cycles," this suite quantifies corporate focus on specific topics through attention scores, aiding economic and financial research.

Crafting personalized shopping experiences at Sephora with innovative data-driven recommendations tailored to individual preferences leveraging tools like CHEMBERT, TF-IDF, and BERT embeddings for precise product insights.

This project is a SMS spam classifier which detect whether the SMS is spam or ham using the multinomial Naive Bayes algorithm along the side of BOW/TF-IDF in NLP

Text Summarization using TF-IDF technique in Python.