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.
Given a document, identifying the closest documents within the list of documents using tf-idf matrix and cosine similarity
Syracuse University, Masters of Applied Data Science - IST 736 Text Mining
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.
A DL project that helps in classifying Toxic Comment weather it is positive or not.
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!
Using text-vectorization and similarity-based-matrix computation
Machine Learning & Natural Language Processing: Reads Classic Novels and Predicts the Author of a Phrase
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.
A simple Python script for transforming a corpus of documents into text vectors suitable for visualization
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.
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 ✨.
A content based movie recommender system.
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