Daniel LaMarco has dedicated his life to technology. He lives in New York, which is arguably among the most high-tech states in the country, and he has watched technology evolve for more than twenty years. He has also watched (and helped) machines learn.

Machine learning isn’t something out of a sci-fi book. It’s something happening on your computers, phones and tablets right now. It is how technology learns and customizes itself. Daniel LaMarco, who knows what to look for, can spot the benefits of machine learning from a simple trip to a New York café. Likewise, you can witness machine learning by interacting with your smartphone or tablet.

Once you understand the basics of how machines learn, which is briefly touched on below, you’ll likely begin to recognize its influence everywhere.

Supervised Learning. With supervised learning, machines use labeled inputs and outputs to anticipate situations in which historical data can predict future events. For example, these machines can identify credit card transactions that are likely to be fraudulent.

Unsupervised Learning. Unsupervised learning resembles supervised, but it operates without labeled outputs or historical data. In other words, it is not given the correct answer. Such learning is useful for tasks like analyzing transitional data.

Intrigued? Machine learning is a basic and logical application of technology, and those with interest in it have the potential to pursue a career similar to Daniel LaMarco’s in IT. You don’t need to live in New York City, but if you want to explore the ever-expanding opportunities in technology careers, you must keep learning. Put your technology to work and educate yourself about the future – you might just find your place in it.

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