Word Embedding (Python) is a technique to convert words into a vector representation. Computers cannot directly understand words/text as they only deal with numbers. So we need to convert words into ...

Think about someone you’d call a friend. What’s it like when you’re with them? Do you feel connected? Like the two of you are in sync? In today’s story, we’ll meet two friends who have always been in ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

As someone who frequently mentors newcomers in machine learning, I’m often asked how to get started. One of the resources I consistently recommend is the keras.io/code examples section. It’s a ...

This project implements a drug-disease association prediction model using Graph Convolutional Networks (GCN) with advanced data augmentation techniques. The model predicts novel drug-disease ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

Earlier this year, scientists discovered a peculiar term appearing in published papers: “vegetative electron microscopy”. This phrase, which sounds technical but ...

Abstract: E-commerce platforms face significant challenges in detecting anomalous products, including counterfeit goods and fraudulent listings, which can undermine user trust and platform integrity.

Abstract: Graph Neural Networks (GNNs) have been proven to be useful for learning graph-based knowledge. However, one of the drawbacks of GNN techniques is that they may get stuck in the problem of ...