Building our first Deep Learning model

Now that we have built a basic NN, it's time to use our knowledge of creating an MLP to build a DL model. You will notice that the core framework will remain the same and is built upon the same foundation.

So, what makes it deep?

While the exact origins of who first used DL are often debated, a popular misconception is that DL just involves a really big NN model with hundreds or thousands of layers. While most DL models are big, it is important to understand that the real secret is a concept called backpropagation.

As we have seen, NNs such as MLPs have been around for a long time, and by themselves, they could solve previously unsolved classification problems such as XOR or give better predictions than traditional classifiers. However, they were still not accurate when dealing with large unstructured data such as images. In order to learn in high-dimensional spaces, a simple method called backpropagation is used, which gives feedback...