This project consists in performing a Topics Modeling as well as a sentiment analysis on user opinions of Android applications. Data is extracted using Web Scrapping from the Google Play Store.

Classify, find categories for, and automatically process complaint emails

Metis project 5/7

A data challenge to analyze news headline to draw insight and build predictive models to predict the kind of reaction different news headlines will receive from readers.

A Python tool that summarizes and categorizes Launch School Capstone YouTube presentations using the YouTube Data API, OpenAI API, NLTK, PyLDAvis, and Streamlit

NLP projects

Segmentação dos principais assuntos das reviews utilizando Latent Dirichlet Allocation (LDA). Pandas, Spacy, Deep Translator, GoogleTranslator, googletrans, NLTK, LDA, WordCloud, Pandarallel, pyLDAvis, sklearn, GridSearchCV.

This project showcase the application of LDA Topic Modelling and KMeans Clustering for extracting information from the PDF documents

Explore & Discover Research Papers on Arxiv repository using Topics learned using LDA using Gensim

LDA Topic Modelling and VADER Sentiment Analyzer

Sentiment Analysis on more than 1 Million Tweets of Gaming During Covid19 with help of Python and NLP

Выполняется тематическое моделирование для отзывов о работе банка с подробным анализом полученных тем

Major concern Identification using Topic Modeling in Telecom Department

Using data science for explaining what is data science..

topic modelling

Topic Modelling with LDA on Journalistic Turkish Texts

This repo contains a demonstration of the Latent Dirichlet Allocation Model (LDA) for topic modelling using Gensim Package, and pyLDAvis to visualize the LDA topics.

Extracting Topics according to relevance using LDA

A Jupyter notebook analyzing the major reasons for Tesla order cancellation and how Elon Musk's tweets correlate with order cancellation.