Apress.Scaled.Forecasting.with.Python.and.R.With.Forecasting.for.Several.Different.Types.of.Models.and.Time.Series-QUiD

Section

Appz

Group

QUiD

Size

1,87 GB

Files

43

Date

2021-01-16

NFO

Release Name : Apress.Scaled.Forecasting.with.Python.and.R.With.Forecasting.for.Several.Different.Types.of.Models.and.Time.Series-QUiD

Publisher    : Safaribooks
Release Date : 2021-01-16
Size         : 41 x 50MB
Url          : https://learning.oreilly.com/videos/scaled-forecasting-with/9781484268933/


Release Info: 
In this video, you will explore forecasting techniques in Python, including how to use machine learning models from Scikit Learn, as well as 
integrating R as a sub process to gain access to the robust forecast library, incorporating the auto.arima and tbats models. We create our own 
Python class called Forecaster that stores all of the relevant information about the predictions, including error metrics, model forms, 
hyperparameter selections, and the forecasts themselves. The module is written in such a way that models can easily be added to the framework 
for increasing accuracy.


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