Since I started doing Data Science a few years ago, I have used more advanced mathematics than I ever thought I would have. And, as I take the classes, that use of mathematics has accelerated.

Given that the math side of Data Science and AI is not going away any time soon, it’s probably best to get good at it.

Fortunately, for all of us Siraj Raval explains how to read math equations in a way that only he can: quickly and awesomely.

Siraj Raval has a great talk on genetic algorithms and neuroevolutionary strategies offer us a way to replicate the process of natural selection en silico.  (Bonus points for the Latin usage, Siraj!)

Google already uses self-creating AI as part of its AutoML service that finds the best model for customers.

Not content to school the world on the wonderful world of AI, Siraj Raval brings his unique teaching style to bare on the mathematics behind cryptography (and, by association, cryptocurrencies).

From the video description:

The math behind cryptography is immensely fascinating, I could spend all day studying it! We’re going to go over some fundamental cryptographic concepts like hashing, zero knowledge proofs, and my favorite ‘ZK-Snarks’. This is quite an in-depth video, i had to pick and choose the topics i wanted to dive into more. There is so, so much i could talk about. Each of these topics could deserve their own course. Cryptography is going to be paramount to building future decentralized Artificial Intelligence systems that we can both control and protect from attackers.

Siraj Raval has a video explaining the Unity and it’s new AI tool.

Creating 3D AI in a simulated world is actually pretty easy using Unity. It’s a powerful tool and I’ll go over its new ML Agents toolkit, that allows researchers and developers to build/train ML models in a 3D simulation. It’s pretty fun watching it in a 3D world, lets break down the code and concepts.