Member-only story
Deep Learning Illustrated, Part 3: Convolutional Neural Networks
An illustrated and intuitive guide on the inner workings of a CNN
Welcome to Part 3 of our illustrated journey through Deep Learning. If you’ve missed the previous articles, definitely go back to read them. They lay the groundwork for what we’re about to dive into today.
To quickly recap, we previously discussed the inner workings of neural networks by building a simple model to predict the daily revenue of an ice cream shop. We found that neural networks can handle complex problems by harnessing the combined power of several neurons. This allows them to uncover patterns in data that might otherwise be hard to recognize. We also learned that neural networks primarily solve two types of problems: Regression or Classification.
Just as we built a revenue prediction model, we can create models to address diverse problems by modifying the structure. Convolutional Neural Networks (CNNs) are specialized models designed for image recognition tasks. However, they rely on the same fundamental principles as the models we have encountered thus far (plus a few more steps). Today, we will explore the inner workings of a CNN and understand exactly what is…
