March 2018
Intermediate to advanced
320 pages
7h 53m
English
book
TensorFlow Deep Learning Projects
by Alexey Grigorev, Srinivas Kulkarni, Rajalingappaa Shanmugamani
Content preview from TensorFlow Deep Learning Projects
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Using regression to predict the future prices of a stock
Given the observation matrix and a real value label, we are initially tempted to approach the problem as a regression problem. In this case, the regression is very simple: from a numerical vector, we want to predict a numerical value. That's not ideal. Treating the problem as a regression problem, we force the algorithm to think that each feature is independent, while instead, they're correlated, since they're windows of the same timeseries. Let's start anyway with this simple assumption (each feature is independent), and we will show in the next chapter how performance can be increased by exploiting the temporal correlation.
In order to evaluate the model, we now create a function ...
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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.