Category: Convolutional Network
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Understanding Convolutional Neural Networks (CNNs) Through Excel
Understanding Convolutional Neural Networks (CNNs) Through Excel Deep learning is often seen as a black box. We know that it learns from data, but we rarely stop to ask how it truly learns. What if we could open that box and watch each step happen right before our eyes? With Excel, we can do exactly…
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Why Are Convolutional Neural Networks Great For Images?
Why Are Convolutional Neural Networks Great For Images? The Universal Approximation Theorem states that a neural network with a single hidden layer and a nonlinear activation function can approximate any continuous function. Practical issues aside, such that the number of neurons in this hidden layer would grow enormously large, we do not need other network architectures. A simple…
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Vision Transformers (ViT) Explained: Are They Better Than CNNs?
Vision Transformers (ViT) Explained: Are They Better Than CNNs? 1. Introduction Ever since the introduction of the self-attention mechanism, Transformers have been the top choice when it comes to Natural Language Processing (NLP) tasks. Self-attention-based models are highly parallelizable and require substantially fewer parameters, making them much more computationally efficient, less prone to overfitting, and…