Practical Time-Series Analysis
Time Series Analysis allows us to analyze data
which is generated over a period of time and
has sequential interdependencies between
the observations. This book describes special
mathematical tricks and techniques which
are geared towards exploring the internal
structures of time series data and generating
powerful descriptive and predictive insights.
Also, the book is full of real-life examples
of time series and their analyses using
cutting-edge solutions developed in Python.
The book starts with descriptive analysis to
create insightful visualizations of internal
structures such as trend, seasonality and
autocorrelation. Next, the statistical methods
of dealing with autocorrelation and non-
stationary time series are described. This is
followed by exponential smoothing to produce
meaningful insights from noisy time series data.
At this point, we shift focus towards predictive
analysis and introduce autoregressive models
such as ARMA and ARIMA for time series
forecasting. Later, powerful deep learning
methods are presented, to develop accurate
forecasting models for complex time series,
and under the availability of little domain
knowledge. All the topics are illustrated with
real-life problem scenarios and their solutions
by best-practice implementations in Python.
The book concludes with the Appendix, with
a brief discussion of programming and solving
data science problems using Python.
Things you will learn:
• Understand the basic concepts of
Time Series Analysis and appreciate its
importance for the success of a data
science project
• Develop an understanding of loading,
exploring, and visualizing time-series
data
• Explore auto-correlation and gain
knowledge of statistical techniques to
deal with non-stationarity time-series
• Take advantage of exponential
smoothing to tackle noise in
time-series data
• Learn how to use auto-regressive
models to make predictions using
time-series data
• Build predictive models on time series
using techniques based on
auto-regressive moving averages
• Discover recent advancements in deep
learning to build accurate forecasting
models for time-series
• Gain familiarity with the basics of
Python as a powerful yet simple to
write programming language
www.packtpub.com
$ 44.99 US
£ 37.99 UK
Prices do not include local sales
Tax or VAT where applicable
Practical Time-Series Analysis Dr. Avishek Pal, Dr. PKS Prakash
Master Time Series Data Processing, Visualization, and
Modeling using Python
Practical
Time Series
Analysis
Dr. Avishek Pal, Dr. PKS Prakash
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