January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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Deep neural networks
Let's recap on what we learned in Chapter 4, Training Neural Networks. A neural network is a machine emulation of the human brain that is seen as a set of algorithms that have been set out to extract patterns out of data. It has got three different layers:
- Input layer
- Hidden layer
- Output layer
Sensory numerical data (in the form of a vector) passes through the input layer and then goes through the hidden layers to generate its own set of perceptions and reasoning to yield the final result in the output layer.
Can you recall what we learned in Chapter 4, Training Neural Networks, regarding the number of layers in ANN and how we count them? When we have got the layers like the ones shown in the following diagram, can ...
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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.
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.