Congratulations! You’ve built a neural network, trained it with gradient descent, and evaluated its performance. But here’s the thing – your first attempt probably isn’t optimal. It’s like baking a cake with the first recipe you found online. It might be edible, but with some tweaking of the ingredients and baking time, it could be amazing. That’s what hyperparameter tuning is all about. by Christopher Miller