MACHINE LEARNING :GOING BEYOND EFFICIENCY AND ADAPTING TO CHANGE
Over the last couple of decades, the technological advances in storage and processing power have enabled some innovative products based on machine learning, such as Netflix’s recommendation engine and self-driving cars. Through the use of statistical methods, algorithms are trained to make classifications or predictions, and to uncover key insights in data mining projects. These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. Machine learning algorithms are typically created using frameworks that accelerate solution development
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The differences :Since deep learning and machine learning tend to be used interchangeably, it’s worth noting the nuances between the two. Machine learning, deep learning, and neural networks are all sub-fields of artificial intelligence. However, neural networks is actually a sub-field of machine learning, and deep learning is a sub-field of neural networks
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Why ML is important to you as a customer ?
Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of
new products. Many of today's top companies, such as Facebook, Google and Uber, make machine learning a central part of their operations. Machine learning has become a significant competitive differentiator for many companies.
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