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Demucs: Advanced Music Source Separation with Hybrid Transformer Technology

by Zainul Abideen | Jul 9, 2025

Introduction to Demucs Demucs is a cutting-edge music source separation model developed by Facebook Research, designed to extract individual components from audio tracks, such as vocals, drums, and bass. Utilizing a Hybrid Transformer architecture, Demucs represents a...

Unlocking the Potential of Graph Neural Networks with PyTorch Geometric

by Zainul Abideen | Jul 9, 2025

Introduction to PyTorch Geometric PyTorch Geometric (PyG) is a library built on top of PyTorch that facilitates deep learning on irregular structures such as graphs and point clouds. With its extensive functionality, PyG is designed to handle complex data structures,...

Building Graph Neural Networks with Spektral: A Comprehensive Guide

by Zainul Abideen | Jul 9, 2025

Welcome to Spektral Spektral is a Python library designed for graph deep learning, built on the Keras API and TensorFlow 2. Its primary goal is to provide a simple yet flexible framework for creating graph neural networks (GNNs). With Spektral, you can tackle various...

Unlocking Insights with PyTorch Captum: A Comprehensive Guide to Model Interpretability

by Zainul Abideen | Jul 9, 2025

Introduction to PyTorch Captum PyTorch Captum is an open-source library designed to provide insights into machine learning models, particularly those built with PyTorch. It enables developers to understand the decisions made by their models through various...

Unlocking AIX360: A Comprehensive Guide to AI Explainability and Interpretability

by Zainul Abideen | Jul 9, 2025

Introduction to AIX360 AIX360 is an open-source toolkit designed to enhance the explainability and interpretability of AI models. With the growing reliance on AI in various sectors, understanding how these models make decisions is crucial. AIX360 provides a suite of...
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