Practical Lessons in Actuarial Science PDF Download
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Author: Miles Menander Dawson
Publisher:
ISBN:
Category : Actuarial science
Languages : en
Pages : 514
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Book Description
Author: Miles Menander Dawson
Publisher:
ISBN:
Category : Actuarial science
Languages : en
Pages : 514
Get Book Here
Book Description
Author: Miles Menander Dawson
Publisher:
ISBN:
Category : Actuarial science
Languages : en
Pages : 510
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Book Description
Author: Detroit Public Library
Publisher:
ISBN:
Category : Dictionary catalogs
Languages : en
Pages : 960
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Book Description
Author: Detroit Public Library
Publisher:
ISBN:
Category :
Languages : en
Pages : 958
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Book Description
Author: Detroit Public Library
Publisher:
ISBN:
Category : Dictionary catalogs
Languages : en
Pages : 960
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Book Description
Contents: 1. 1889-1893.--2. 1894-1898.--3. 1899-1903.
Author: Detroit Public Library
Publisher:
ISBN:
Category : Catalogs, Dictionary
Languages : en
Pages : 960
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Book Description
Author:
Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 436
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Book Description
Author: New York Public Library. Research Libraries
Publisher:
ISBN:
Category : Library catalogs
Languages : en
Pages : 578
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Book Description
Author: R.R. Bowker Company. Department of Bibliography
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 904
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Book Description
Author: Steven S. Skiena
Publisher: Springer
ISBN: 3319554441
Category : Computers
Languages : en
Pages : 456
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Book Description
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
