Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, (Paperback)
Practical guidance on applying statistical methods to data science
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, (Paperback)
Vara #: 31161279

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, (Paperback)

Vara #: 31161279

ISK 8498

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What Stands Out

Cross-Platform Tools
Utilizes both R and Python, offering flexibility and accessibility for data scientists, enabling them to choose the best tool for their specific tasks and projects.
Essential Concepts
Covers over 50 critical statistical concepts, ensuring a solid foundation for understanding and applying statistics in real-world data science scenarios, enhancing practical skills.
Practical Examples
Includes practical examples and applications that help translate theoretical concepts into actionable insights, making it easier for readers to apply statistical techniques effectively.

Upplýsingar um vöru

Shop Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, (Paperback) online at a best price in Iceland. 739269750
  • Comprehensive examples in Python for practical statistical guidance
  • Bridges the gap between statistical methods and data science in an accessible format
  • Emphasizes the importance of exploratory data analysis in data science
  • Explains the principles of experimental design for obtaining definitive answers
  • Covers key classification and machine learning techniques for data prediction
  • Includes unsupervised learning methods for extracting meaning from unlabeled data
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateJune, 2020
Pages360
Reading levelProfessional and Scholarly
SubgenreData Science
Series titleNo Series
Edition2nd Edition
PublisherO'Reilly Media
Original languagesEnglish
LanguageEnglish
Edu focusMathematics
Is collectibleN
Binding typePerfect Binding
Recording time0 min
Retail packagingSingle Piece
Assembled product dimensions (l x w x h)7.00 x 0.90 x 9.10 in (17.8 x 2.3 x 23.1 cm)
Assembled product weight1.3 lb (590 grams)
Bisac subject headingComputers

Who Should Buy?

Suitable For
  • Data Science Students

    This book is ideal for students learning data science concepts and wanting practical applications using R and Python.

  • Professional Analysts

    Data analysts looking to enhance their statistical knowledge and apply it practically will benefit from this book.

  • Self-Learners

    Individuals teaching themselves data science can leverage the clear explanations and examples to grasp essential statistical concepts.

Not Suitable For
  • Beginner Statisticians

    Those new to statistics may find the content too advanced without a foundational understanding of the subject.

  • Advanced Researchers

    Experienced researchers may not find new insights or advanced techniques relevant to their work in this book.

  • Non-Technical Readers

    Users without a background in programming or statistics may struggle with the technical jargon and examples provided.

VÖRULÝSING

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, (Paperback)

About This Item

Introducing "Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python Edition 2 Paperback" – the comprehensive guidebook that every aspiring and experienced data scientist needs in their arsenal. Authored by Peter Bruce, Andrew Bruce, and Peter Gedeck, this book is an invaluable resource for anyone looking to master the world of data science. With the rapid advancement of technology and the ever-increasing importance of data-driven decision making, proficiency in statistics is no longer optional for data scientists. This book covers 50 essential statistical concepts, providing you with a solid foundation to solve real-world problems using R and Python. Whether you are a beginner just starting on your data science journey or a seasoned professional seeking to expand your knowledge, this book has something for everyone.

The authors have carefully curated the content to ensure that the concepts are presented in a practical and accessible manner, making it easy for readers to grasp and apply statistical techniques. The publication date of May 2020 ensures that this book is up-to-date with the latest advancements and best practices in the field of data science. It is formatted as a paperback, making it convenient for you to carry it with you wherever you go. By delving into the pages of "Practical Statistics for Data Scientists," you will gain a deep understanding of statistical concepts such as hypothesis testing, regression analysis, machine learning, and much more. The authors provide clear explanations, step-by-step examples, and code snippets in R and Python, allowing you to implement what you learn directly in your projects. With its focus on practical application, this book is a must-have for any data scientist.

Gain the knowledge and skills you need to excel in your career, enhance your decision-making abilities, and unlock valuable insights from your data. Don't miss out on this opportunity to enhance your data science toolkit. Order your copy of "Practical Statistics for Data Scientists: 50 Essential Concepts Using R and Python Edition 2 Paperback" today and embark on your journey towards becoming a master data scientist.

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Spurningar og svör viðskiptavina

  • spurningu: Does the book cover basic statistics?

    svara: Yes, the guide covers basic statistics from a data science perspective.
  • spurningu: What is the format of the book?

    svara: The book is available in paperback format.
  • spurningu: Who are the authors of the book?

    svara: The authors of the book are Peter Bruce, Andrew Bruce, and Peter Gedeck.

Peter Bruce All Books Editorial Review

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Kostir

  • Clear explanations of concepts
  • Practical examples in R and Python
  • Great for beginners and experts
  • Helpful exercises and problems
  • Covers a wide range of topics

Gallar

  • Some topics may feel repetitive.

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