智能营销机器学习指南（英文版）

The Smart Marketer's Guide toMachine LearningWhat’s data got to do with it?Man v. Machine: Battle of the BrainsWhat does the future hold?How’s machine learning being used today?What’s the difference between AI and ML?ContentsWhat exactly is machine learning?Future predictions range from apocalyptic (robots will destroy the human race!) to utopian (robots will make everything about our lives better). But intelligent machines have already become an integral part of our lives, quietly inserting themselves into our daily routines. We talk to them in our homes (Alexa, what’s today’s forecast?), they tell us what movies we might like (thanks, Netflix), and pretty soon they’ll be driving us to and fro (see you soon, Waymo).Far from titanium skeletons with menacing red eyes, or human replicas with wires and microchips just below the surface, these machines are invisible and yet all around us — in our smart devices, powering our Google searches, and helping us to do and achieve more than ever before.One of the most important developments that’s driving the artificial intelligence (AI) boom is machine learning. Machine learning has applications far and wide, like enabling the highly personalized marketing that’s possible today. Yet many haven’t heard of it, or don’t understand it, or even fear it. As Marie Curie once said, “Nothing in life is to be feared, it is only to be understood.”Let’s demystify machine learning and find out how it’s impacting today’s world, including commerce marketing.Welcome to the second machine age.For decades, the rise of machines— and what that means for humans — has been a hot topic.mach.ine / learn.ingMachine learning (ML) is a form of artificial intelligence (AI) that enables computers to learn without explicit programming. Instead of telling a computer everything it needs to know to complete a task, ML can enable a computer to essentially “figure it out for itself”, using data to learn. The more data a computer is fed, the more it learns and the smarter it gets, improving its accuracy and ability to complete tasks over time. Google Brain, Google’s artificial intelligence research project, was one of the first to successfully use ML to identify an object — specifically an image of a cat. The research team built a neural network of 16,000 computer processors and showed it 10 million random images from YouTube as a training exercise. They then showed it 20,000 different items and found that, without being told what a cat is, the network began correctly identifying all the cat images. The important point here is that the data was unlabeled. There were no images labeled “cat”, no programs explaining what a cat looks like. The system honed in on cats without ever being told to do so. Machine learning is exciting because it makes it possible to analyze huge amounts of data and take action with a speed and precision that humans simply can’t match. Like setting bids or making trades in milliseconds…or looking at 10 million pictures