Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

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 ...

Deep Learning Crash Course: A Hands-On, Project-Based Introduction to Artificial Intelligence is written by Giovanni Volpe, Benjamin Midtvedt, Jesús Pineda, Henrik Klein Moberg, Harshith Bachimanchi, ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

This project implements a neural network from scratch to classify handwritten digits using the MNIST dataset. The neural network is built using Python and utilizes libraries such as NumPy and ...