Many chapters feature "live" neural networks. You can click to change weights or biases and see the cost function react in real-time. This tactile learning is lost in a PDF.
If you are struggling to grasp the intuition behind neural networks, stop scrolling web pages. Download the PDF, open a notebook, and start annotating. It transforms a great resource into a personal textbook that will serve you for the rest of your AI career.
It is widely considered one of the best entry points into the field. But if you are bouncing between a web browser tab and your code editor, you are doing it wrong. There is a growing consensus among students and developers:
Before we praise Nielsen, we must diagnose the pain point. Most current resources (YouTube crash courses, Medium articles, or dense academic tomes like Deep Learning by Goodfellow et al.) suffer from three fatal flaws:
Introduction to neural nets using the MNIST digit recognition problem.
http://neuralnetworksanddeeplearning.com