In this article, we will discuss how to implement sentiment analysis on a raw tweets dataset in python, find the polarity scores to classify the sentiments, and train a Long short-term memory (LSTM) and Convolutional Neural Network to predict the sentiment polarity and compare the results. Reference

“ Semantic search is a data-searching technique to determine the intent and contextual meaning of words similar to the human mind ”

TLDR — Ensembling keyword and embedding models for search is one of the quickest and easiest ways to improve search performance over the standard embedding based search paradigms. There is a large amount of evidence in the machine learning literature which supports that this helps with in domain performance, out of domain generalization, as well as multilingual transfer. The reason for this seems to be that sparse and dense representations of text seem to represent complimentary linguistic qualities of their […]

AI-Generated image of an ancient robot using Stable Diffusion.