Abstract: Automated classification of learner-generated text to identify behavior, emotion, and cognition indicators, collectively known as learning engagement classification (LEC), has received ...

Abstract: Natural language processing (NLP) has become somewhat well-known because of its many uses; deep neural networks have driven major developments. Still, there are difficulties, especially in ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

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Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Unlock automatic understanding of text data! Join our hands-on workshop to explore how Python—and spaCy in particular—helps you process, annotate, and analyze text. This workshop is ideal for data ...

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ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

In this tutorial, we present a complete end-to-end Natural Language Processing (NLP) pipeline built with Gensim and supporting libraries, designed to run seamlessly in Google Colab. It integrates ...

This is a Natural Language Processing (NLP) application that provides comprehensive analysis of text input, including various statistics and visualizations. The application is available both as a ...