Deep Learning: the new electricity
Have you ever used Google’s photo search feature? Type in ‘cat’ and it will pretty reliably bring up any cats in your photo collection. It’s not perfect – it mistakes Land Rovers for cats some of the time – but it’s getting better all the time. And that is the point of machine learning. Among much else, machine learning, a subset of which is called deep learning, now powers Google photo search, speech recognition on Android, and video recommendations on YouTube. Neural networks think more like us than digital computers do, so they can get smarter at serving up content to us and translating what we say or type. As well as image and speech recognition, deep learning algorithms hold much promise in medical diagnosis and drug development.
Chinese-American computer scientist Andrew Ng is a leading light in machine learning and deep learning. A professor at Stanford University, he founded the Google Brain Deep Learning Project, which developed large scale neural networks using Google’s distributed computing power. On his lunch breaks Ng also founded Coursera to offer free online courses to everyone.
Ng’s machine learning teachings were condensed into Coursera’s very first course in 2011, and since then 1.5 million people have taken it. In June 2017 he announced deeplearning.ai, a new learning gateway to building a career in artificial intelligence. Ng likes to compare AI to electricity, noting that ‘with the rise of electricity, we saw the rise of the electrical engineering discipline’ (Techcrunch.com). An unabashed AI evangelist, he describes deep learning in the same terms Tesla used to speak of electricity: ‘Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.’
As well as a thorough grounding in neural networks and deep learning, Ng’s Coursera offering includes a deep learning specialisation consisting of five courses centred around case studies in healthcare, autonomous driving, sign language reading, music generation and natural language processing. These are ‘hard’ problems that computers were still unable to solve just a couple of decades ago, but which deep learning now shows promise of cracking.
Demand for machine learning experts far outstrips supply, so these courses, which come ‘straight from the horse’s mouth’ in the form of the major figure of Andrew Ng, are a gateway to an exciting career.