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Thursday, August 30, 2018

Deep Learning for Time Series Forecasting

Like Jason's style of clear motivations  and short tutorials.  You can get free samples of his writing below.

Jason Brownlee's New Book: 
Deep Learning for Time Series Forecasting
Predict the Future with MLPs, CNNs and LSTMs in Python
Deep Learning for Time Series Forecasting
$37 USD

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.

In this new Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math, research papers and patchwork descriptions about time series forecasting with deep learning algorithms.

With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

About this Ebook:

Read on all devices: PDF format Ebook, no DRM.
Tons of tutorials: 5 parts, 25 step-by-step lessons, 575 pages.
Real-world projects: 2 large end-to-end tutorial projects.
Many datasets: Univariate, multivariate, multi-step, and more.
Working code: 131 Python (.py) code files included.
Clear, Complete End-to-End Examples.
Convinced? ....  "

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