Machine Learning Deep Dive #1: Bayesian Decision Theory
Welcome to the first article of the “Machine Learning Deep Dive” biweekly series. Each article will consist of a theoretical summary based on Ethem Alpaydın’s Machine Learning book. For each method, there will be a separate GitHub repository containing sample codes and examples prepared from the scratch and/or using the open-source Python libraries. Wish you pleasant reading!
Read more
Twitter Sentiment Analysis
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
Read more
Introduction to VECTOR EMBEDDING
VECTOR EMBEDDING : it’s a technique for learning numerical representations for token (word) that approximate their lexical meaning.these representations are learned by observed words in their context of occurrence in large volumes of data.
Read more
The State of Multilingual AI
Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. At the same time, a wave of NLP startups has started to put this technology to practical use. While such language technology may be hugely impactful, recent models have mostly focused on English and a handful of other languages with large amounts of resources. […]
Read more