Deep Neural Networks for Supervised Learning: Regression
In Chapters 1 and 2, we explored the topic of DL and studied how DL evolved from ML to solve an interesting area of problems. We discussed the need for DL frameworks and briefly explored a few popular frameworks available in the market. We then studied why Keras is special and spent some time playing around with its basic building blocks provided to develop DNNs and also understood the intuition behind a DL model holistically. We then put together all our learnings from the practical exercises to develop a baby neural network for the Boston house prices use case.