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Data Science Fundamentals for Python and MongoDB
Get Free Ebook Data Science Fundamentals for Python and MongoDB
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From the Back Cover
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms. The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained.Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky†at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced. What You'll Learn:Prepare for a career in data scienceWork with complex data structures in PythonSimulate with Monte Carlo and Stochastic algorithmsApply linear algebra using vectors and matricesUtilize complex algorithms such as gradient descent and principal component analysisWrangle, cleanse, visualize, and problem solve with dataUse MongoDB and JSON to work with data
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About the Author
Dr. David Paper is a full professor at Utah State University in the Management Information Systems department. He wrote the book Web Programming for Business: PHP Object-Oriented Programming with Oracle and he has over 70 publications in refereed journals such as Organizational Research Methods, Communications of the ACM, Information & Management, Information Resource Management Journal, Communications of the AIS, Journal of Information Technology Case and Application Research, and Long Range Planning. He has also served on several editorial boards in various capacities, including associate editor. Besides growing up in family businesses, Dr. Paper has worked for Texas Instruments, DLS, Inc., and the Phoenix Small Business Administration. He has performed IS consulting work for IBM, AT&T, Octel, Utah Department of Transportation, and the Space Dynamics Laboratory. Dr. Paper's teaching and research interests include data science, process reengineering, object-oriented programming, electronic customer relationship management, change management, e-commerce, and enterprise integration.
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Product details
Paperback: 228 pages
Publisher: Apress; 1st ed. edition (May 11, 2018)
Language: English
ISBN-10: 9781484235966
ISBN-13: 978-1484235966
ASIN: 1484235967
Product Dimensions:
6.1 x 0.5 x 9.2 inches
Shipping Weight: 12 ounces (View shipping rates and policies)
Average Customer Review:
4.7 out of 5 stars
14 customer reviews
Amazon Best Sellers Rank:
#1,261,792 in Books (See Top 100 in Books)
IMHO, it's a cheap trick for the author to include MongoDB in its title as the DB was used in a couple of cases at the end of the book. It's a show stopper for me because I was interested in how MongoDB can be used in data science and this book does not answer that.
This is a great read for anyone who has experience in software development but has just begun exploring the data science field. The book doesn't use complex data science jargon which can be sometimes imitating to beginners. The extensive Python code examples provided in the book are easy to follow and generate the output to help understand data science concepts. Looking forward to the next series for intermediate level data scientist.
I have had the privilege of working directly for David Paper as a GA at Utah State University. As part of the classes he turned me onto this book at a good technical resource. Dave is has a well articulated writing style where he likes to show the reader how to be successful at something instead of getting heavy theory and non application. Though my review could be taken with a grain of salt as I have a professional relationship directly with the author I still feel that this book would be a great read for a go getter looking to change the world.
Data Science Fundamentals for Python and MongoDB is brilliant. David Paper does an amazing job of explaining difficult material in a simple way. The integration with MongoDB is next level. Anyone who is interested in data science would benefit greatly by the work presented in this book.
Amazing read. Really easy to understand. Good Coding examples are also provided.I am a practicing data science professional and I think this book is really good for all levels of expertise.
Data Science is a great opportunity for those who are interested in python or mongoDB. It has great examples that makes it easy to follow. Most of the books if not all, they are so hard to learn their matrials, but with this book it has everything I need in a very simple way to understand. So. I believe that it's the best way to learn python.
Honestly I really like the book it has a good explanation and examples and every chapter you go through you can understand it easily and if you do the examples while you are reading the book you will get the idea what he is talking about. Good job Dave :)
This book as the perfect way to sgart learning python. It start easy and goes deep in the material fast so you will learn fast. I recommend this book to anyone that wants to learn python.
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