Math is a crucial skill for people who are interested in Data Science and Machine Learning. Until now, most of the people who are doing Data Science have a strong background in math, usually, people with master or Ph.D. degrees.
However, this fact seems to change in the next years, after the hype of Machine Learning we are facing a process of democratization. Now the door of Data Science is open for everyone.
To truly madly deeply understand how the machine learning algorithms work we need to understand some mathematical concepts. In this tutorial, I would like to share my experience in the process of learning some of those concepts.
What I want to do is build a bridge between those concepts and Python, more specifically, SciPy and NumPy and TensorFlow. Basically is just another tutorial about vectorization, in this case, oriented to understand and implement machine learning algorithms and the mathematical foundation that supports it.
The material of the talk can be found here
If you like this website, please upvote my Awesome Python pull request.