The Theoretical and Practical Foundations of Machine Learning. Master Matrices, Linear Algebra, and Tensors in Python

What you'll learn

Understand the fundamentals of linear algebra, a ubiquitous approach for solving for unknowns within high-dimensional spaces.
Manipulate tensors using the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch
Possess an in-depth understanding of matrices, including their properties, key classes, and critical ML operations
Develop a geometric intuition of what’s going on beneath the hood of ML and deep learning algorithms.
Be able to more intimately grasp the details of cutting-edge machine learning papers