NLP unleashed: unleashing the power of natural language processing.

by Alper Özöner and Ali Utku Aydın This week, we have made some progress on the model selection as well as the representation of the eye tracking data we obtained from our EyeTribe eye tracker. First off, we have finally solved the problem of reading the raw data and its formatting. Amusingly, the formatting of    

You might have noticed the dust on images in the icons and AWS UI. These are screenshot from 2016 (gulp), so reproducing these exact steps will be challenging to say the least. For example, at the time I felt generous enough to try Atom as my text editor — the redeeming value is that at least it was an Electron app. But S3 explorer? Fast forward five years, and, with some minor exceptions, it can still server as a valid […]

Amazon Sagemaker is a very popular service by AWS for building, training, and deploying machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. In this post, I will use Amazon Sagemaker to build a binary text classification model using bert-base-uncasedmodel on

Photo by Nick    

GloVe (Global Vectors) was proposed by Pennington, Socher, and Manning in 2014. It is a new global log-bilinear regression model that combines the advantages of the count-based and the prediction-based models. If you are new to word embedding models, feel free to check out my previous post on the    

Build a News Article Classifier using the PySpark framework