Full-featured information retrieval system that indexes and enables searching through the CACM (Communications of the ACM) corpus.
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Updated
Feb 28, 2025 - HTML
Full-featured information retrieval system that indexes and enables searching through the CACM (Communications of the ACM) corpus.
Interactive NLP-based AI system designed to manage cinema bookings and provide a seamless user experience.
Retrieve Information from Text Documents with TF-IDF model and dimention reduction with (Latent Semantic Indexing)LSI.
In this notebook we analyze and classify news articles using machine learning techniques, including Logistic Regression, Naive Bayes, Support Vector Machines, and Random Forests. Explore text vectorization and NLP for accurate news categorization.
I developed a sophisticated ML model using LLMs to predict user preferences in chatbot interactions.implemented a comprehensive data preprocessing pipeline,including feature extraction and encoding,to optimize performance. conducted extensive hyperparameter tuning and evaluation, enhancing accuracy and in AI-driven conversational systems.
AniVerse: A comprehensive anime recommendation platform with a React/Next.js frontend, Node.js backend for user management, and a Python/Flask API for personalized recommendations.
AI-powered chatbot using NLP & Machine Learning (Logistic Regression) with TF-IDF vectorization and a Streamlit interface. Trained on predefined intents and logs conversations.
Build a Web App called AI-Powered Recipe Recommender App
System to recommend movies based on user-inputted movie
Tool for processing, categorizing, and searching through PDF documents and images using unsupervised K-means clustering and OCR.
This Spam Detection model classifies emails as spam or not using TF-IDF and Logistic Regression. It includes evaluation metrics and sample tests. The repository provides the complete code and dataset for easy use and modification.
The purpose of this project is to build a machine learning model to classify SMS messages as either "spam" or "ham" (not spam). Using TF-IDF vectorization and LinearSVC, it reads an SMS dataset, transforms text data into numerical features, and trains a model to distinguish between spam and ham. The "SMSSpamCollection" dataset has labeled messages.
Predicting the topic of news articles
Sentiment analysis done over Customer Reviews using Various ML Models. It includes preprocessing, TF-IDF vectorization, model evaluation, and a lightweight script to load trained models and make predictions on custom inputs.
Spam Email Detector
A Machine Learning project to detect spam messages using Natural Language Processing (NLP), TF-IDF vectorization, SMOTE for imbalance handling, and a Logistic Regression classifier — all wrapped up in Streamlit web app.
Repository for the course Essentials in Text and Speech Processing Fall 2024
Market trends and investment insights
Built an end-to-end text classification model using TF-IDF vectorization and models like Logistic Regression and SVM. Includes exploratory data analysis, model evaluation
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