Neural Network Course Intro (IUST) — Feedforward, Loss & Backprop Basics

Kick off the Neural Network course at Iran University of Science and Technology (IUST) with Mr. Ala. In this intro lecture, we clarify what neural networks are, how feedforward works, the role of loss functions and optimization (gradient descent), and the basics of backpropagation you’ll use all semester.

Whether you’re new to machine learning or refreshing the fundamentals, this session sets you up for success in Fall 2025. Save the playlist, grab the slides, and follow along with coding labs.

What you’ll learn:

What a neural network is and where it’s used

The feedforward pass and activations

Loss functions, optimization, and gradient descent intuition

Backpropagation (chain rule) at a high level

Recommended prerequisites:
Linear algebra, calculus (chain rule), Python/NumPy.
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