Browsing Tag
neural network
57 posts
What Are Hyperparameters in the Context of Neural Networks?
Early on in my deep learning journey, I confused “parameters” and “hyperparameters” more times than I’d like to…
Weight Initialization in Neural Networks: Concepts, Math, and Practice
Introduction It’s easy to overlook weight initialization as a mere technical formality — after all, the network is…
Training and Optimization in Neural Networks: A Complete Guide
Training a neural network is a bit like teaching someone to shoot free throws by only giving them…
What Is a Convolutional Neural Network (CNN) and How Does It Work?
If you’ve ever used Face ID to unlock your phone, had Google Photos automatically tag a picture of…
What Is the Role of Dropout in Neural Network Training?
Anyone who’s trained a neural network on a small dataset has probably run into a frustrating pattern: training…
What Techniques Can Be Used to Mitigate the Vanishing Gradient Problem?
Once you understand why the vanishing gradient problem happens — small derivatives multiplying together across many layers until…
What Is the Vanishing Gradient Problem in Neural Networks?
For years, one puzzling issue held deep learning back: adding more layers to a network should make it…
How Do Convolutional Neural Networks (CNNs) Differ from Traditional Neural Networks?
“Just use a neural network” is common advice for beginners starting out in machine learning, but it glosses…
What Is the Difference Between a Feed-Forward and a Recurrent Neural Network?
If you’ve ever wondered why a network that can perfectly classify photos of cats and dogs struggles badly…
Applications of Neural Networks: From Theory to Real-World Impact
Neural networks stopped being a purely academic topic the moment they started outperforming humans at narrow, well-defined tasks.…