Hello all, this is a fourth blog post in the Machine learning in Perl series, focusing on the AI::MXNet, a Perl interface to Apache MXNet, a modern and powerful machine learning library.

So, what features does a neural network ACTUALLY learn?
I had no clue about the answer or how to find it until 3blue1brown released a set of videos about neural networks. It was Grant Sanderson’s take at explaining the subject to newcomers. Maybe even he felt that there were some missing pieces in the explanation by other people and that he could address them in his tutorials.

Google's Machine Learning Crash Course has already been delivered to more than 18,000 Googlers and now it it have been made available for free and to all as part of Learn with Google AI, a new educational resource aimed at every developer.

When data scientist Joel Grus wrote an article on using machine learning to solve the "fizzbuzz" problem last year, most people saw it as an exercise in comedy, perhaps with a warning about the inappropriate use of AI. But we saw a deeper lesson. Certainly, you don’t need AI to solve fizzbuzz, so long as someone tells you the algorithm underlying the problem. But suppose you discover a seemingly random pattern like fizzbuzz output in nature? Patterns like that exist throughout real life, and no one gives us the algorithm. Machine learning solves such problems.

Tinker With a Neural Network Right Here in Your Browser.
Don’t Worry, You Can’t Break It. We Promise.