Movie Recommender based on Content based filtering.

Resume Matcher: A Streamlit app that compares resumes with job descriptions, highlights matched and missing skills, and calculates text similarity and skill coverage.

Text Classification of Legitimate and Rogue Online Privacy Policies: A manual analysis and an experimental procedure

A DL project that helps in classifying Toxic Comment weather it is positive or not.

A diploma project focused on vectorizing scientific texts using the Top2Vec algorithm, with the aim of analyzing thematic groups, identifying trends, and visualizing the dynamics of interest in various topics in the field of computer science.

Homeworks and final project for Infosearch course

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.

Predictive Text Analysis project! This repository contains code for predicting answers to science exam questions using advanced natural language processing techniques. Check out the code and results!

A content based movie recommender system.

IMDB movie review classification using neural network (text-vectorization v/s word-embeddings)

Using text-vectorization and similarity-based-matrix computation

A movie recommendation system using content-based filtering with cosine similarity to suggest movies based on plot and genre similarity. Built with Python, Pandas, and Scikit-learn.

The repository contains notebooks created for collecting and preprocessing the corpus of diary entries and for experiments on creating models for predicting gender, age groups of authors and the time period of text creation.

Syracuse University, Masters of Applied Data Science - IST 736 Text Mining

🧠 Machine Learning & Natural Language Processing: Predict the author of literary text snippets. Built with TensorFlow and Keras, this project trains an LSTM model on classic literature to identify writing style and authorship.

The project finds the emotion in the given text. It takes input in a text/sentence format through the User or through Twitter API.

A dynamic Movie Recommender web app using ML text vectorization technique to suggest the user with similar kind of movies and their posters.

Comprehensive guide to text preprocessing and vectorization techniques for NLP, covering tokenization, n-grams, Bag-of-Words, TF-IDF, and related feature-engineering methods.

Sentiment Analysis is a Natural Language Processing (NLP) technique used to identify the emotional tone behind a piece of text — typically classified as positive, negative, or neutral.

Natural language learning codes