PDF Ebook , by Deepti Gupta
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, by Deepti Gupta
PDF Ebook , by Deepti Gupta
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Product details
File Size: 15189 KB
Print Length: 424 pages
Publisher: Apress; 1st ed. edition (August 3, 2018)
Publication Date: August 3, 2018
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07FZG3PRG
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Amazon Best Sellers Rank:
#966,637 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
I am so pleased to have found this book. It is an excellent road map which:- Provides a clear explanation of real world business problems, analytical techniques, and the direct application ofData Science in multiple industry verticals.- Offers a hands on opportunity with data files and the underlying source code in both SAS and R.- Includes the guidance of a very talented instructor and successful Data Scientist who also has the ability to clearly communicate the underlying thought process behind the coding and applied mathematics to provide a meaningful business solution.I would highly recommend this book to anyone who would like to improve their business acumen, familiarity with SAS/R, and problem solving ability.
I was searching a book on data science with applied real time case studies and finally i got this book!!The book is easy to follow simple.A lot of complex plots and figures are very clearely explained by author.Having access to real datasets and codes is big plus.i would definately recommended it to anyone aspiring to be data scientists.
This book focuses on real time industrial business problems and practical analytical approaches to solve those problems by implementing predictive models and machine learning techniques . The writing is lucid and the case studies are instructive , which can be easily understood and can be used as a reference. As this book contains detailed explanation about 7 most leading industries like banking, healthcare, retail, airline etc so it is very helpful for any data scientist (beginners & experienced). I would definitely recommend this book to all aspiring data scientist. Great Book!
This book is thorough, easy to understand, and more importantly very interesting. It is excellent for machine learning references in R and SAS. The case studies are very well explained. Playing with the sources code and data will help a lot any beginner. I highly recommend it.
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