Data Science Fundamentals for Python and MongoDB

David Paper

ISBN 10: 1484235967 / ISBN 13: 9781484235966

Edité par Apress, Apress, 2018

A propos de cet article

nach der Bestellung gedruckt Neuware - Printed after ordering - Build the foundational data science skills necessary to work with and better understand complex data science algorithms. Thisexample-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 MongoDBis 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 LearnPrepare 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 dataWho This Book Is ForThe 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.

N° de réf. du vendeur 9781484235966

Détails bibliographiques

• Titre: Data Science Fundamentals for Python and MongoDB
• Éditeur: Apress, Apress
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 1484235967
• ISBN à 13 chiffres: 9781484235966
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

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.

À propos de l?auteur

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.