http://ghafoorsblog.com/categories/neuralnetworks/Recent content in Neuralnetworks on Ghafoor's Personal BlogHugoennoreply@example.com (AG Sayyed)noreply@example.com (AG Sayyed)Copyright © 2024-2026 AG Sayyed. All Rights Reserved.Sat, 16 May 2026 17:25:52 +0100http://ghafoorsblog.com/courses/ibm/ai-developer-content/ai-developer-pcert/02-introduction-to-ai/02-module/006-neural-networks/Fri, 11 Jul 2025 01:16:42 +0000noreply@example.com (AG Sayyed)http://ghafoorsblog.com/courses/ibm/ai-developer-content/ai-developer-pcert/02-introduction-to-ai/02-module/006-neural-networks/<p class="lead text-primary"> Neural networks are computational models inspired by the human brain, consisting of interconnected layers of artificial neurons. This document explores the structure and function of neural networks, the training process using forward and backward propagation, and the main types of neural networks, including perceptron, feed-forward, convolutional, and recurrent networks. Key applications and the role of activation functions are also discussed. </p> <hr> <h2 id="introduction-to-neural-networks">Introduction to Neural Networks</h2> <p>Neural networks are foundational components of artificial intelligence, modeled after the structure of the human brain. They consist of interconnected nodes, or neurons, that process and transmit information. By learning from data, neural networks can recognize patterns, make decisions, and improve over time.</p>