December 2018
Intermediate to advanced
394 pages
10h 26m
English
Content preview from Keras 2.x Projects
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Time series models
In the previous section, Time series analysis, we explored the basics behind time series. To perform correct predictions of future events based on what happened in the past, it is necessary to construct an appropriate numerical simulation model.
Choosing an appropriate model is extremely important as it reflects the underlying structure of the series. In practice, two types of models are available: linear or nonlinear. These can be selected based on whether the current value of the series is a linear or nonlinear function of past observations.
The following are the most widely used models for forecasting time series data:
- AR (autoregressive)
- MA (moving average)
- ARMA (autoregressive moving average)
- ARIMA (autoregressive ...
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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.