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 DeepLearning.ai 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.

Artificial Intelligence has transformed vision technology! Carl and Richard talk to Tim Huckaby about his latest work with vision systems for retail, security and more. Tim talks about how AI has fundamentally changed the way you implement vision systems, taking away many of the limitations on number of people tracked, object and face recognition and so on. The conversation digs into the demonstration done at the Build conference for using regular security cameras to implement a real-time safety tracking system on a construction site – aspirational, but coming soon! And of course, there’s a long conversation about privacy. What is fair, reasonable and wise?

Listen Now –>

 

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.

In this episode of the AI show Erika explains how to create deep learning models with music as the input. She begins by describing the problem of generating music by specifically describing how she generated the appropriate features from a midi file. She then describes the deep learning model she used in order to generate music.

Learn more: