Applied Deep Learning: A Case-based Approach To... -

Each method is paired with real-world examples to demonstrate theoretical concepts in action. Target Audience

and Mathematicians looking for fundamental properties and a "from-scratch" understanding.

The book by Umberto Michelucci (published by Apress) is a practical guide designed to bridge the gap between complex mathematical theory and hands-on application. Core Content & Structure Applied Deep Learning: A Case-Based Approach to...

Encourages learning by doing, including implementing logistic regression from scratch using NumPy before moving to libraries like TensorFlow .

This 2018 title was followed by (2019), which builds on these foundations to cover specialized topics like object detection with Keras. ICAART 2021 - tutorials Each method is paired with real-world examples to

The book focuses on helping practitioners and students understand the "inner workings" of neural networks through a series of case studies:

Readers should have basic undergraduate-level mathematics (Analysis) and intermediate knowledge of Python . Key Takeaways & Learning Goals Core Content & Structure Encourages learning by doing,

interested in the mathematical theory behind neural networks.