Deep Learning with Yacine on MSN
Deep Neural Network from Scratch in Python – Fully Connected Feedforward Tutorial
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Taylor Stanberry, a Naples native, won the 2025 Florida Python Challenge, removing 60 Burmese pythons. The annual competition aims to control the invasive python population in Florida. This is the ...
Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s abilities, ...
Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...
Abstract: This brief introduces the Inverse-free hybrid spatial-temporal derivative neural network (IHSTDNN), a novel neural network that integrates principles from gradient neural networks (GNN) and ...
Abstract: In this paper, we propose a robust end-to-end classification model, Graph-in-Graph Neural Network (GIGNet), for automatic modulation recognition (AMR). In GIGNet, multi-level graph neural ...
The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...
The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...
This is my journey to implement NNs from first principles, one neuron at a time. In this notebook we build a neural network with 2 neurons in layer 1, and 1 neuron in layer 2. We then visualize how it ...
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