June 2019
Intermediate to advanced
308 pages
7h 21m
English
Content preview from Hands-On Deep Learning for IoT
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FAQs
In this section, we will cover some frequently asked questions (FAQs), which will help you to extend this application:
- Can we use other deep architectures to make predictions in similar IoT settings?
Answer: Yes, using other deep architectures could be a viable option. For example, creating a convolutional-LSTM network by combining the predictive power of both CNN and LSTM layers has proven to be effective in many use cases, such as audio classification, natural language processing (NLP), and time-series forecasting.
- Sometimes we do not have enough IoT data to train the model flexibly. How can we increase the amount of training data?
Answer: There are many ways to do this. For example, we can try to generate the training set by ...
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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.
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.
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.