Think of deep learning as an art of cooking. One way to cook is to follow a recipe. But when we learn how the food, the spices, and the fire behave, we make our creation. And an understanding of the "how" transcends the creation.

Likewise, an understanding of the "how" transcends deep learning. In this spirit, this book presents the deep learning constructs, their fundamentals, and how they behave. Baseline models are developed alongside, and concepts to improve them are exemplified.

Topics covered in the book include:

- Multilayer Perceptrons
- Long- and short-term Memory Networks
- Convolutional Neural Networks
- Autoencoders.

Every topic is thoroughly explained and illustrated graphically. Moreover, implementations in TensorFlow are given for developing a complete understanding.