Data Science Fundamentals for Python and MongoDB - David Paper

Data Science Fundamentals for Python and MongoDB

(Autor)

Buch | Softcover
214 Seiten
2018 | 1st ed.
Apress (Verlag)
978-1-4842-3596-6 (ISBN)
32,09 inkl. MwSt
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 science

Work with complex data structures in Python

Simulate with Monte Carlo and Stochastic algorithms

Apply linear algebra using vectors and matrices

Utilize complex algorithms such as gradient descent and principal component analysis

Wrangle, cleanse, visualize, and problem solve with data

Use MongoDB and JSON to work with data


Who This Book Is For

The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentalsthat are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.

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.

1. Introduction.- 2. Monte Carlo Simulation and Density Functions.- 3. Linear Algebra.- 4. Gradient Descent.- 5. Working with Data.- 6. Exploring Data.

Erscheinungsdatum
Zusatzinfo 117 Illustrations, black and white; XIII, 214 p. 117 illus.
Verlagsort Berkley
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Netzwerke
Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Web / Internet
Schlagworte data cleansing • Data Science • Data Visualization • data wrangling • Gradient descent • heat map • JSON • linear algebra • MongoDB • Monte Carlo simulation • Normal distribution • NoSQL • Python NumPy Library • Python Pandas Library • randomness • Simulation • Stochastic Simulation • Uniform distribution • Vector and Matrix Math
ISBN-10 1-4842-3596-7 / 1484235967
ISBN-13 978-1-4842-3596-6 / 9781484235966
Zustand Neuware
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