APMTH 226 - Theory of Neural Computation Learning Course

[APMTH 226 - Theory of Neural Computation Learning Course] APMTH 226 - Theory of Neural Computation: APMTH 226 explores the theoretical foundations of neural computation, focusing on mathematical models and algorithms that underpin the functioning of neural networks. Topics include neural dynamics, learning rules, and information processing in biological and artificial neural systems. The course integrates principles from mathematics, neuroscience, and computer science to analyze how neural networks encode and process information. Through theoretical study, computational exercises, and modeling projects, students gain insights into the fundamental mechanisms of neural computation and their applications in artificial intelligence, robotics, and cognitive science. The course prepares students for advanced research and development in neural network theory and applications. This Learning Course is a platform that helps students to study and learn. The platform provides all the required material for the students to study. The material includes Study guide, Exam Questions & Answers, Study Notes and other resources that are useful for the students. It also gives information about the upcoming exams so that students can prepare themselves accordingly.