A few years ago, there was a shift in the world of machine learning.
Companies, such as Skytree and Context Relevant, began popping up, promising to make it easier for companies outside of big banks and web giants to run machine learning algorithms and to do it at a scale congruent with the big data promise they were being pitched. Soon, there were many startups promising bigger, faster, easier machine learning. Machine learning became the new black as it became baked into untold software packages and services — machine learning for marketing, machine learning for security, machine learning for operations, and on and on and on.
Eventually, deep learning emerged from the shadows and became a newer, shinier version of machine learning. It, too, was very difficult and required serious expertise to do. Until it didn’t. Now, deep learning is the focus of numerous…
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