Anybody new to machine learning will initially find it a confusing space, given the overlap of artificial intelligence, machine learning, expert systems, neural networks, supervised and unsupervised techniques, and deep learning. Below are a number of links to places you might want to start exploring. This list is not necessarily representative of every important initiative in this field; that said it's a useful point to pivot from. For details of current research into machine learning applications in threat and anomaly detection see my postgrad research.
Fundamentals
'Artificial Intelligence (AI)' | Wikipedia
'Intelligent Agent (IA)' | Wikipedia
'Machine Learning' | Wikipedia
'Rule Based Programming' | Wikipedia
'Supervised Learning' | Wikipedia
'Unsupervised Learning' | Wikipedia
'Reinforcement Learning' | Wikipedia
'Information Theory' | Wikipedia
'Turing Completeness' | Wikipedia
'Artificial Neural Network (ANN)' | Wikipedia
Video Tutorials: Introductory
These are arranged with introductory material first and more complex material later.
'Machine Learning Lecture 1' YouTube | Andrew Ng | Standford University | Jul 22 2008
'Machine Learning for Video Games' YouTube | Seth Bling | Jun 13 2015
'How Deep Neural Nets Work' YouTube | Brandon Rohrer | Mar 2 2017
'Lecture 10 - Neural Networks' YouTube | Yaser Abu-Mostafa | Caltech | May 6 2012
'Backpropagation: how it works' YouTube | Victor Lavrenko | Aug 31 2015
Video Tutorials: Deep Learning
'The Next Generation of Neural Networks' YouTube | Geoffrey Hinton | GoogletechTalks | Nov 29 2007
'Introduction to Deep Learning & Deep Belief Nets' YouTube | Geoffrey Hinton | Aug 24 2015
'Deep Learning, Self-Taught Learning and Unsupervised Feature Learning' | Andrew Ng | Aug 24 2015