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Since the concept of “machines learning” was introduced in the 1950s, the field has gone from a cryptic domain understood by a few (Turing, Markov, Legendre, Laplace or Bayes) to a technology that every company must deploy.
Every day we hear how data and automation improve our shopping experiences, our online searches and enables fraud prevention and cybersecurity routines to do more, faster and better for us.
Now, the amalgamates created around Artificial Intelligence, Machine Learning and Big Data are bound to confuse industry observers or investors who aren’t familiar with the technical details. If you’re asking yourself: “What’s the difference between Big Data and Machine Learning?”, then for the sake of my piece, simply think about it this way: “Big Data is Machine Learning’s great uncle”. Machine Learning doesn’t need Big Data to exist. But, if it uses it, it can benefit greatly from its vast knowledge.
Big Data is Machine Learning’s great uncle. Machine Learning doesn’t need Big Data to exist. But, if it uses it, it can benefit greatly from its vast knowledge”
I’m sure you’ll find more sophisticated answers out there but what matters most is not just the technology. It’s how technology is applied. So rather than discuss typical enterprise use cases that might bore you to death, I thought I’d highlight interesting (and somewhat unexpected) scenarios where data and machine learning play a role.
Drones as flying data collectors
You might not think of drones as having anything to do with data and machine learning. But they’re beginning to have a huge impact in a number of industries from mining to construction to farming.