Books
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V Lakshmanan, Data Science on the Google Cloud Platform, O'Reilly Media, Inc., 2017. ISBN: 9781491974551
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). With this practical guide, author and GCP Program Manager Valliappa Lakshmanan shows you how to gain insight into a sample business decision by applying different statistical and machine learning methods and tools. Along the way, you’ll get an extensive tour of the big data and machine learning parts of GCP. [read online on Safari Books (O'Reilly media)] [order on Amazon] |
V. Lakshmanan, Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human and Environmental Applications. Springer, 2012. ISBN: 978-94-007-4074-7.
The aim of this book is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution satellite imagery or from any data is that can be placed on a spatial grid.The book is based off a course that I taught in Spring 2011 at the University of Oklahoma to a diverse group of graduate students from Computer Science, Meteorology and Environmental Engineering. It should be suitable as a textbook for upper-level undergraduate students and graduate students.
Even though the material developed out of a graduate course, this book is targeted primarily at practitioners i.e. people who need to solve a problem and are looking for ways to address it. Hence, the book forgoes detailed descriptions of theory and mathematical development in favor of more practical issues of implementation.
A software implementation in the Java programming language is included for nearly all the techniques discussed in this book.
[read online at Springer].
Order a $25 print copy of the book. This works only if you access it from an University IP address.
[Order on Amazon]
The aim of this book is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution satellite imagery or from any data is that can be placed on a spatial grid.The book is based off a course that I taught in Spring 2011 at the University of Oklahoma to a diverse group of graduate students from Computer Science, Meteorology and Environmental Engineering. It should be suitable as a textbook for upper-level undergraduate students and graduate students.
Even though the material developed out of a graduate course, this book is targeted primarily at practitioners i.e. people who need to solve a problem and are looking for ways to address it. Hence, the book forgoes detailed descriptions of theory and mathematical development in favor of more practical issues of implementation.
A software implementation in the Java programming language is included for nearly all the techniques discussed in this book.
[read online at Springer].
Order a $25 print copy of the book. This works only if you access it from an University IP address.
[Order on Amazon]
V. Lakshmanan, E. Gilleland, A. McGovern, and M. Tingley, eds., Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the Fourth International Workshop on Climate Informatics. Springer, 2015.
This is an edited volume of contributed papers that arose out of Climate Informatics 2014. I was program chair of this conference, and this was the first year that we were able to put together such a collection of papers representing the state of the science.
[read online at Springer].
This is an edited volume of contributed papers that arose out of Climate Informatics 2014. I was program chair of this conference, and this was the first year that we were able to put together such a collection of papers representing the state of the science.
[read online at Springer].
