November 2018
Intermediate to advanced
322 pages
7h 54m
English
Content preview from TensorFlow Machine Learning Projects
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Transfer learning
Learning in humans is a continuous process—whatever we learn today is built upon the learning we have had in the past. For example, if you know how to drive a bicycle, you can extend the same knowledge to drive a motorcycle, or drive a car. The driving rule remains the same—the only thing that changes is the control panel and actuators. However, in deep learning, we often start afresh. Is it possible to use the knowledge the model has gained in solving a problem in one domain, to solve the problem in another related domain?
Yes, it's indeed possible, and it's called transfer learning. Though a lot of research is still going on in the field, a great deal of success has been achieved in applying transfer learning in the area ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.