Search in ebookee.net!

Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python

ISBN: 1788290224

标签: 数据库



The poster (email) is not available. 收藏推荐: Bookmark this: Practical Time Series Analysis Master Time Series Data Processing Visualization and Modeling using Python

图书介绍



Practical Time Series Analysis Master Time Series Data Processing Visualization and Modeling using Python

Dr. Avishek Pal, "Practical Time-Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python"
2017 | ISBN-10:1788290224 | 244 pages | PDF | 12 MB



Step by Step guide filled with real world practical examples.

About This Book

Get your first experience with data analysis with one of the most powerful types of analysis-time-series.
Find patterns in your data and predict the future pattern based on historical data.
Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide

Who This Book Is For

This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods.

What 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

In Detail

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.

Style and approach

This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.
DOWNLOAD
(Buy premium account for maximum speed and resuming ability)









[Directly Download] Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python!


Download this book

使用ezdownloader下载
DOWNLOAD


Copyright Disclaimer:
本站一切内容源于互联网搜索,禁止商用! 如有任何不妥请联系:admin@ebookee.com,我们将在24小时内删除相关内容。

浏览量:0 添加时间:2018-06-21 11:03:42, 更新时间:2018-06-21 11:03:42, shared by nokia241186

搜索该书!...


Search mirrors of "Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python"...

Search in ebookee.com!

下载链接


Free Magazine Subscriptions & Technical Document Downloads

推荐:使用EZdownloader下载电子书


没有下载链接
请在图书介绍里查找下载链接,如果没有,可以试着搜索有无其它该书信息。

不能下载?
如果不能下载或者在“图书介绍”中找不到 "Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python" 的下载链接请留言。下次访问本站时察看 所有留言 看是否有人已经更新了该书。

该书可能有其它下载链接,请点 这里查询相关图书


相关链接


"Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python" 相关链接:

  1. Ebooks list page : 36483
  2. Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python
  3. Practical Time-Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python
  4. [PDF] Introducing Data Science: Big Data, Machine Learning, and more, using Python tools
  5. Evaluating the Measurement Uncertainty: Fundamentals and Practical Guidance (Series in Measurement Science and Technology) - Removed
  6. Analysis of Single-Cell Data ODE Constrained Mixture Modeling and Approximate Bayesian Computation
  7. Analysis of Single-Cell Data ODE Constrained Mixture Modeling and Approximate Bayesian Computation
  8. [PDF] Practical Plant Failure Analysis: A Guide to Understanding Machinery Deterioration and Improving Equipment Reliability
  9. [PDF] Big Data, MapReduce, Hadoop, and Spark with Python: Master Big Data Analytics and Data Wrangling with MapReduce Fundamentals using Hadoop, Spark, and Python
  10. [PDF] Analysis of Single-Cell Data: ODE Constrained Mixture Modeling and Approximate Bayesian Computation (BestMasters)
  11. Practical Plant Failure Analysis: A Guide to Understanding Machinery Deterioration and Improving Equipment Reliability (repost) - Removed
  12. Practical Plant Failure Analysis: A Guide to Understanding Machinery Deterioration and Improving Equipment Reliability - Removed
  13. Real-Time Digital Signal Processing: Implementations and Applications
  14. Practical Plant Failure Analysis: A Guide to Understanding Machinery Deterioration and Improving Equipment Reliability - Removed
  15. Discrete-Time Speech Signal Processing: Principles and Practice (repost)
  16. Real-Time Digital Signal Processing : Implementations and Applications (Repost)
  17. Practical Plant Failure Analysis: A Guide to Understanding Machinery Deterioration and Improving Equipment Reliability - Removed
  18. Real-time Digital Signal Processing: Implementations and Applications
  19. Real-Time Digital Signal Processing : Implementations and Applications
  20. Real Time Digital Signal Processing Implementations and Applications
  21. Real Time Digital Signal Processing Implementations and Applications Jun 2006

Comments


"Practical Time-Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python" 没有评论.

    Leave a Comment

    如果没有下载链接或者下载链接无效,请查看相关链接或者搜索相关资料。

    required

    required

    email addresses

    required

    Not clear? Click to refresh.


    Back to Top