Overview 7 computer science courses that are structured to provide you with a deeper understanding of concepts and practical hands-on experience.A wide range of ...

Finding the right book can make a big difference, especially when you’re just starting out or trying to get better. We’ve ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

Abstract: Spiking neural networks (SNNs) are attractive algorithms that pose numerous potential advantages over traditional neural networks. One primary benefit of SNNs is that they may be run ...

2 Deep neural network architectures In this Research Topic, three articles address practical identification problems through the proposal of novel DL network architectures. The first article by ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

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 ...

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

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 ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...