January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Summary
In this chapter, we introduced the basic ideas and models for using a neural network to learn distributed word representation. We particularly dove into the Word2Vec model and have shown how to train a model, as well as how to load the pre-trained vectors for downstream NLP applications. In the next chapter, we will talk about more advanced deep learning models in NLP, such as recurrent neural network, long-term short memory model, and several real-world applications.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.