Introduction - Building a Convolutional Neural Network with Keras
Note: This Guided Project is part of our Practical Deep Learning for Computer Vision with Python course, and is meant to solidify the knowledge from the previous lesson - Guide to Convolutional Neural Networks in which we cover the theory and history of CNNs.
Time to put the theory into practice! If it didn't all fit into place already, there's a good chance it will now that you can build and see the results. If not - don't worry! Once the practical application is finished, try revisiting the initial explanations in the lesson. Many people have an "a-ha" moment after practicing with CNNs an then re-reading the introductory parts.
Note: With high-level APIs such as Keras that do the heavy lifting, it's easy to forget how things work under the hood, and it's worth revisiting them in the initial phases of learning (as well as some time down the line). If you haven't had any exposition to some of the terminology used here, it might take you a bit of time to get things to click. It's easy to conect the dots looking backwards, but not so much looking forwards. This is how discoveries are made!