A Python toolbox for gaining geometric insights into high-dimensional data

Word Factor Vectors

📖 Use Bi-normal Separation to find document vectors which is used to compute similarity for shorter sentences.

The project has text vectorization, handling big data with merging and cleaning the text and getting the required columns while boosting the performance by feature extraction and parameter tuning for NN, compares the Performances through applied different models treating the problem as classification and regression both.

🚀 Course Recommendation System is a machine learning-powered web application designed to recommend similar courses from Coursera's vast dataset of over 3,000 courses. Built using Python, Scikit-learn, and Streamlit, the app preprocesses course data, applies text vectorization, and leverages cosine similarity to offer personalized recommendations.

Given a document, identifying the closest documents within the list of documents using tf-idf matrix and cosine similarity

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.

This project is an unsupervised NLP-based recipe recommender system designed to provide personalized recipe suggestions. The system employs content-based filtering techniques, utilizing cosine similarity to measure the resemblance between user inputs and a database of recipes.

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

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

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.

Comment Sentiment Analysis using Deep Learning

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.

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!

Hands-on labs and solutions from AWS Academy's Machine Learning for Natural Language Processing course — covering text vectorization, sentiment analysis, entity recognition, topic modeling, and multilingual NLP using AWS ML services.

Explore advanced neural networks for crafting captivating headlines! Compare LSTM 🔄 and Transformer 🔀 models through interactive notebooks 📓 and easy-to-use wrapper classes 🛠️. Ideal for content creators and data enthusiasts aiming to automate and enhance headline generation ✨.

Using text-vectorization and similarity-based-matrix computation

🧠 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.

A simple Python script for transforming a corpus of documents into text vectors suitable for visualization

Machine learning-based sentiment analysis system that classifies movie reviews as positive or negative using NLP techniques and text classification models.