January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Fine-tuning
Fine-tuning refers to the technique of initializing a network with parameters from another task (such as an unsupervised training task) and then updating these parameters based on the task at hand. For example, NLP architecture often uses pre-trained word embeddings such as Word2Vec, and these word embeddings are then updated during training or through continued training for a specific task such as sentiment analysis.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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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.