Practical Time Series Analysis
Prediction with Statistics and Machine Learning
|Price||$31.99 - $79.99
|Format||Paper book / ebook (PDF)|
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase.
Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges
in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly.
You'll get the guidance you need to confidently: Find and wrangle time series data; Undertake exploratory time series data analysis; Store temporal data; Simulate time series data; Generate and select features for a time series; Measure error; Forecast and classify time series with machine or deep learning; Evaluate accuracy and performance.
4 5 23
by Ted Dunning, Ellen Friedman
Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors T...
Price: $21.94 | Publisher: O'Reilly Media | Release: 2014
by Venkat Reddy Konasani, Shailendra Kadre
Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios.The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors - both SAS, statistics, analytics, and big data experts - first show how SAS is us...
Price: $31.10 | Publisher: Apress | Release: 2015
by Butch Quinto
Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main techno...
Price: $33.51 | Publisher: Apress | Release: 2018
by Robert I. Kabacoff
R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also m...
Price: $17.58 | Publisher: Manning | Release: 2015
by David Taieb
Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights.Industry expert David Taieb bridges th...
Price: $39.99 | Publisher: Packt Publishing | Release: 2018
by Matt Harrison, Theodore Petrou
The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking...
Price: $39.99 | Publisher: Packt Publishing | Release: 2020
by Karthik Ramasubramanian, Abhishek Singh
Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if y...
Price: $31.74 | Publisher: Apress | Release: 2019
by Gergely Daroczi, Michael Puhle, Edina Berlinger, Peter Csoka, Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Varadi, Agnes Vidovics-Dancs
Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a div...
Price: $23.99 | Publisher: Packt Publishing | Release: 2013