Category: NLP

Word Embeddings vs TF-IDF: Answering COVID-19 Questions

From: https://towardsdatascience.com/word-embeddings-vs-tf-idf-answering-covid-19-questions-703e3d99f783 A comparison of text similarity methods for answering COVID-19 questions. Dataset: CORD-19 Questions we are interested in: Data on potential risks factorsSmoking, pre-existing pulmonary diseaseCo-infections (determine whether co-existing respiratory/viral infections make the virus more transmissible or virulent) and other co-morbiditiesNeonates and pregnant womenSocio-economic and behavioral factors to understand the economic impact of the virus … Continue reading Word Embeddings vs TF-IDF: Answering COVID-19 Questions →

Attention Mechanism in Deep Learning : Simplified

From: https://medium.com/@prakhargannu/attention-mechanism-in-deep-learning-simplified-d6a5830a079d What exactly is the attention mechanism? Look at the image below and answer me, what is the color of the soccer ball? Also, which Georgetown player, the guys in white, is wearing the captaincy band? [Source] When you were trying to figure out answers to the questions above, did your mind do this … Continue reading Attention Mechanism in Deep Learning : Simplified →

Visualizing the Emotional Arcs of Movie Scripts Using Rule-Based Sentiment Analysis

From: https://towardsdatascience.com/visualizing-the-emotional-arcs-of-movie-scripts-using-rule-based-sentiment-analysis-1016b4b1af5a How I used Python, D3 and Flask to create this interactive visualization Almost 72 years ago, acclaimed American writer Kurt Vonnegut came up with a novel method for graphing the plot lines of stories as part of his master’s thesis in anthropology. Although his work was ultimately rejected by the University of Chicago “because it was … Continue reading Visualizing the Emotional Arcs of Movie Scripts Using Rule-Based Sentiment Analysis →