The theory and math behind machine learning are beautiful,
and I want to show this to you.

My journey in machine learning has been full of twists and turns. By training, I am a mathematician. During my PhD, I was doing research in approximation theory, a field close to the heart of learning algorithms.

I saw the stunning applications of machine learning in the life sciences, I was hooked. Since then, I am passionate about neural networks and their inner workings. I love taking them apart piece by piece, understanding every cog in the machine, then putting it all back together.

I believe that to really understand something, you have to build it by yourself from scratch. This is why I am writing a book about the mathematics of machine learning, guiding you from introductory linear algebra to implementing a neural network from scratch.