Build Your First Neural Network in Python - Basic Concepts Only
Using PyTorch
Want to understand neural networks but feel overwhelmed by the math?
In this video, I’ll walk you through the basics of neural networks using Python and PyTorch, with zero complex equations.
As a data engineer, I know the challenges of approaching AI concepts without a research or mathematics background. That’s why this guide focuses on practical, high-level understanding. What You’ll Learn:
Core Concepts: Neurons, layers, loss functions, and backpropagation.
Step-by-Step Walkthrough: How to implement a neural network for XOR in PyTorch.
Training Loop Essentials: How all the pieces come together to train your network.
By the end of this video, you'll understand the foundation of neural networks better than most and feel confident applying them in real-world scenarios.
If you want to dive deeper, I’ve included links to some of the best math-focused neural network resources. Let me know what you think in the comments—feedback is always welcome!