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Time series forecasting in python, marco peixeiro

749 грн

Описание

Build predictive models from time-based patterns in your data. Master
statistical models including new deep learning approaches for time series
forecasting.

In Time Series Forecasting in Python you will learn how to:

Recognize a time series forecasting problem and build a performant predictive
model

Create univariate forecasting models that account for seasonal effects and
external variables

Build multivariate forecasting models to predict many time series at once

Leverage large datasets by using deep learning for forecasting time series

Automate the forecasting process

Time Series Forecasting in Python teaches you to build powerful predictive
models from time-based data. Every model you create is relevant, useful, and
easy to implement with Python. You’ll explore interesting real-world datasets
like Google’s daily stock price and economic data for the USA, quickly
progressing from the basics to developing large-scale models that use deep
learning tools like TensorFlow.

about the technology

You can predict the future—with a little help from Python, deep learning, and
time series data! Time series forecasting is a technique for modeling time-
centric data to identify upcoming events. New Python libraries and powerful
deep learning tools make accurate time series forecasts easier than ever
before.

about the book

Time Series Forecasting in Python teaches you how to get immediate, meaningful
predictions from time-based data such as logs, customer analytics, and other
event streams. In this accessible book, you’ll learn statistical and deep
learning methods for time series forecasting, fully demonstrated with
annotated Python code. Develop your skills with projects like predicting the
future volume of drug prescriptions, and you’ll soon be ready to build your
own accurate, insightful forecasts.

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