Choose the Right One: Evaluating Topic Models for Business IntelligencePython tutorial for evaluating top-notch bigram topic models in customer email classificationApr 27Apr 27
Published inTDS ArchiveTopic Modelling in Business Intelligence: FASTopic and BERTopic in CodeA comparison of two cutting-edge dynamic topic models solving consumer complaints classification exerciseJan 223Jan 223
Published inTowards AIDynamic Visualization of Blockchain NetworkIntroduction to dynamic network visualization with an example of 0.3 million Bitcoin transactionsSep 1, 20241Sep 1, 20241
Published inTDS ArchiveBigram Word Cloud Animates Your Data StoriesHands-on tutorial explaining how to create an Animated Word Cloud of bigram frequencies to display a text dataset in an MP4 videoMay 8, 20241May 8, 20241
Published inTDS ArchiveTopic Modelling with BERTtopic in PythonHands-on tutorial on modeling political statements with a state-of-the-art transformer-based topic modelApr 1, 20242Apr 1, 20242
Published inPython in Plain EnglishEND-to-END Latent Dirichlet Allocation in PythonA practical introduction to LDA modeling with bigram frequencies in PythonFeb 21, 2024Feb 21, 2024
Published inTDS ArchiveData Storytelling with Animated Word CloudsAnimated word clouds turn classic word clouds into a dynamic visualization. Learn more about telling data stories in Python.Nov 22, 20231Nov 22, 20231
Published inTowards AIResearch Article Meta-data Description Made Quick and EasySummarize essential information from research meta-data with text mining methods in a few lines of Python codeJul 30, 2023Jul 30, 2023
Published inPython in Plain EnglishFinVADER: Sentiment Analysis for Financial ApplicationsFinVADER is a Python library extending the popular VADER sentiment classifier with two financial lexicons. Learn more in this tutorial.Jun 8, 2023Jun 8, 2023
Published inTowards AIFine-tuning VADER Classifier with Domain-specific LexiconsExtending the core VADER sentiment classifier’s lexicon with two financial lexicons improves sentiment classification accuracy from 58 % to…May 13, 2023May 13, 2023
