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

A content based movie recommender system.

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!

Using text-vectorization and similarity-based-matrix computation

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

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.

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

Evaluation of the accuracy of vectorization and text classification methods

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.

Clustering text using text vectorization

demistifying nlp with a series of nlp implementation notebooks.

This is a Content-based Movie Recommendation App wherein the user can type in a particular movie that he/she has enjoyed and can get the names and posters of top 5 similar movies.

Discussion about Probabilities, Classification and Zipf's law

This program is a project carried out in the Natural Language Processing course, which is a Taylor Swift song recommender. It utilizes topics such as sentiment analysis in texts, text vectorization, and the removal of stopwords.

Movie Recommender System leverages a content-based approach, suggesting films to users based on the attributes of movies they have previously enjoyed. By analyzing movie metadata such as genre, cast, director, keywords, etc., this project offers personalized recommendations aligned with users' cinematic tastes.

In this project, task involves analyzing the content of the articles to extract key concepts and themes that are discussed across the articles to identify major themes/topics across a collection of BBC news articles.

Tag prediction on Stack Overflow using TensorFlow Keras and Text Vectorization

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

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.