Dr Jason Browniee’s Machine Learning Mastery is for everybody, even total beginners, who’ve heard the hype about ML, and want to get in on the action. It’s step by step, simple and very easy to follow.
Once one has done quite a few chapters into Machine Learning Mastery it’s good to check out ujjwalkarn’s Github list of Machine Learning and Deep Learning Tutorials.
If you’re totally new to neural networks, Andrej Karpathy’s Hacker’s Guide to Neural Networks is hands down the best. No complex formulas, no jargon, just plain and simple concepts demonstrated with code (which you should definitely rewrite to fully understand).
Genetic Algorithms for tuning the weights of an existing neural network: pretty cool, although this is just one way to train a neural network. I’d imagine one would use the gradients in Karpathy’s tutorial to get to a pretty well trained neural network, and then use the genetic algorithm to make small improvement tweaks from there.