This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...
Treescope is an interactive HTML pretty-printer and N-dimensional array ("tensor") visualizer, designed for machine learning and neural networks research in IPython notebooks. It's a drop-in ...
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Backpropagation in neural networks step-by-step explained
Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...
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Build a deep neural network from scratch in Python
We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...
Abstract: Ordered statistics decoding has been instrumental in addressing decoding failures that persist after normalized min-sum decoding in short low-density parity-check codes. Despite its benefits ...
Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...
Abstract: This study introduces a novel strategy for waste segregation employing Convolutional Neural Networks (CNNs) and Python programming. By harnessing CNNs’ image feature extraction capabilities, ...
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