Unsupervised machine learning exploration of NBA topics on Twitter.
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Updated
Apr 18, 2020 - Jupyter Notebook
Unsupervised machine learning exploration of NBA topics on Twitter.
Text clustering in spark with scala using LDA Model on a TF-IDF matrix
Using the foundation and understanding of my first approach to song sentiment analysis using lyrics, created a more robust and better approach to this problem.
Topic-modeling on large data (1.85M tweets written in Spanish, ~1M "Spain geolocated", about 'coronavirus' between 2019 to 2020-04-20). Forked from ShuaiW/twitter-analysis (adapted for Python3 to use a discriminative score), mainly for Twitter LDA (Latent Dirichlet allocation using Gibbs sampling, https://lda.readthedocs.io/)
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
A Case Study On The Rising Omicron Cases and Public Sentiment Analysis using Twitter Data
Topic modeling using Word2Vec and LDA algorithm with Python
Code Repository for the assignments required for the Natural Language Processing master's course at PSUT.
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