Machine learning is the science of programming computers so they can learn from data.In machine learning systems can learn from data, identify patterns and make decisions with minimal human intervention. Examples of ML include the spam filter that flags messages in your email, the recommendation engine Netflix uses to suggest content you might like, and the self-driving cars being developed by Google and other companies.
Machine learning today is not like machine learning of past It was born from pattern recognition to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development. Here are a few widely publicized examples of machine learning applications you may be familiar with:
- The heavily hyped, self-driving Google car? The essence of machine learning.
- Online recommendation offers such as those from Amazon and Netflix? Machine learning applications for everyday life.
- Fraud detection? important uses in our world today.
To get the most value from machine learning, you have to know how to pair the best algorithms with the right tools and processes.
“Humans can typically create one or two good models a week; machine learning can create thousands of models a week.”
– Thomas H. Davenport
While machine learning algorithms have been around for decades, they’ve attained new popularity as artificial intelligence (AI) has grown in prominence. Deep learning models in particular power today’s most advanced AI applications.
Machine learning platforms are among enterprise technology’s most competitive realms, with most major vendors, including Amazon, Google, Microsoft, IBM and others, racing to sign customers up for platform services that cover the spectrum of machine learning activities, including data collection, data preparation, model building, training. As machine learning continues to increase in importance to business operations and AI becomes ever more practical in enterprise settings, the machine learning platform wars will only intensify.
Machine learning affects home life as Machine learning and the IoT is enhancing the way we communicate and live our daily lives.The automation of our domestic lives is already occurring. Amazon’s Echo and Alexa allow for the voice-activated control of your smart-home the dimming of lights, closing of blinds, locking of doors, etc., all at your command. In the very close future, we can expect the automation of practically every aspect of your home. having your favorite song playing as you step through the door.
And the car that drive you home? It drive you.
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