and Mathematicians looking for fundamental properties and a "from-scratch" understanding.
interested in the mathematical theory behind neural networks. 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
Covers essential topics like activation functions (ReLU, sigmoid, Swish), linear and logistic regression, and neural network architectures. linear and logistic regression
The book emphasizes the importance of how to split datasets into train, dev, and test sets to solve real-world problems effectively.
This 2018 title was followed by (2019), which builds on these foundations to cover specialized topics like object detection with Keras. ICAART 2021 - tutorials
Encourages learning by doing, including implementing logistic regression from scratch using NumPy before moving to libraries like TensorFlow .