Deep Learning - Artificial Neural Networks with Tensorflow - Outline

This course focuses on teaching Tensorflow 2 through an API-first, practice-oriented approach. While math is present, it is optional and meant to aid intuition. The course requires basic Python skills and familiarity with numpy and matplotlib. It covers machine learning concepts, including regression, classification, and neural networks, with optional sections on loss functions and gradient descent.

What is the significance of understanding the Tensorflow 2 API in this course?

How can students fill in gaps in their knowledge during the course?

What is the purpose of the optional sections on loss functions and gradient descent?