Time Series with Python: Practical Time Series Analysis, Forecasting, Prediction and Machine Learning Models with Python.

by Jim Smith

Time Series Analysis with Python
A time series is a sequence of observations over a certain period. The simplest example of a time series that all of us come across on a day to day basis is the change in temperature throughout the day or week or month or year.
The analysis of temporal data is capable of giving us useful insights on how a variable changes over time.

This book will teach you how to analyze and forecast time series data with the help of various statistical and machine learning models in elaborate and easy to understand way!
This book is for those who are looking to understand time series and time series forecasting models from scratch. At the end of this book you will have a good understanding on time series modelling.

What you will Learn:

Introduction Data Processing and Visualization Modeling Parameter Calibration Naïve Methods Moving Average ARIMA Exponential Smoothing Walk Forward Validation Prophet Model LSTM Model Error Metrics Applications

Tags:--

time series prediction python multivariate time series forecasting python
time series analysis in python with statsmodels
time series machine learning python
python time series prediction example
python resample time series
time series model python

55 pages, Kindle Edition

Published July 31, 2019

About the author

Librarian Note: There is more than one author in the GoodReads database with this name.

Jim Smith, the laziest (yet still professional) teacher in town, is a head of school, education consultant, Independent Thinking Associate, speaker and bestselling author.