Time Series with Python

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Time Series with Python: Practical Introduction to Time Series Forecasting, Prediction and Machine Learning Models with Python
by Jim Smith
English | 82 pages | EPUB | 785 KB

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



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