Data Science from Scratch 2e: First Principles with Python
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Data Science from Scratch 2e: First Principles with Python
Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch
Data Science from Scratch 2e: First Principles with Python
Numéro d'article: 83824005

Data Science from Scratch 2e: First Principles with Python

88% des répondants recommanderaient ceci à un ami

Numéro d'article: 83824005

BIF 195658

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Ce qui se démarque

Comprehensive Foundation
Offers readers a solid understanding of data science concepts, ensuring they grasp fundamental principles before diving into advanced topics, making it perfect for beginners and self-learners.
Python Focused
Utilizes Python to teach data science, providing hands-on coding examples that reinforce learning and equip readers with practical skills highly valued in the industry.
Accessible Learning
Breaks down complex data science topics into digestible lessons, ensuring that readers without a formal background can successfully engage with and apply the material.

Détails du produit

Shop Data Science from Scratch 2e: First Principles with Python online at a best price in Burundi. 1492041130
  • Updated for Python 3.6, this second edition of Data Science from Scratch focuses on mastering data science tools and understanding the principles underlying them
  • Authored by Joel Grus, the book is designed to help readers with mathematics, statistics, and programming skills to get started as a data scientist
  • Includes new material on deep learning, statistics, and natural language processing
  • Provides a crash course in Python and covers the basics of linear algebra, statistics, and probability as used in data science
  • Teaches how to collect, explore, clean, and manipulate data, as well as dive into the fundamentals of machine learning and implement various models
  • Covers topics like recommender systems, natural language processing, network analysis, MapReduce, and databases
Publisher Ou2032Reilly
Publication date 30 April 2019
Edition 2nd
Language English
Print length 403 pages
ISBN-10 1492041130
ISBN-13 978-1492041139
Item weight 712 g
Dimensions 17.53 x 2.29 x 23.11 cm

À qui est-ce destiné ?

Suitable For
  • Beginners in Data Science

    Ideal for those who want to learn data science principles without prior knowledge or complex jargon.

  • Python Programmers

    Perfect for individuals already familiar with Python programming looking to expand their skills towards data science.

  • Self-learners

    Great for self-taught individuals seeking a structured introduction to data science concepts and methods.

Not Suitable For
  • Advanced Data Scientists

    Not suitable for those with extensive experience in data science seeking advanced or specialized techniques.

DESCRIPTION DU PRODUIT

Data Science from Scratch 2e: First Principles with Python

About This Item

Are you interested in diving into the world of data science with Python? Look no further than "Data Science from Scratch: First Principles with Python 2nd Edition." This book is perfect for beginners who want to learn Python data science principles and techniques. Whether you're a student, a professional looking to upskill, or someone who simply has a passion for data analysis, this book is a must-have. The second edition offers updated material and a comprehensive introduction to data science concepts using Python. Learn how to harness the power of Python to extract insights from data and uncover patterns that will drive decision-making. With easy-to-follow explanations and step-by-step examples, you'll quickly gain a solid foundation in Python data science. The book covers a wide range of topics, including data visualization, statistical analysis, machine learning, and much more.

With its hands-on approach, you'll not only understand the theory behind data science but also apply it to real-world projects. Whether you're a complete beginner or already have some experience with Python, "Data Science from Scratch: First Principles with Python 2nd Edition" is written in a way that makes complex concepts accessible. You'll feel confident in your ability to tackle data science problems head-on. So, if you're ready to unlock the potential of Python for data science, order your copy of "Data Science from Scratch: First Principles with Python 2nd Edition" today. Start your journey to becoming a proficient Python data scientist and gain the skills needed to succeed in this rapidly growing field.

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Questions et réponses des clients

  • question: What is the focus of the book?

    répondre: The focus is to help readers master the principles and tools of data science
  • question: What topics are covered in the book?

    répondre: Python, linear algebra, statistics, probability, machine learning models and techniques, deep learning, natural language processing are covered, among others
  • question: Is the book updated for the latest version of Python?

    répondre: Yes, the second edition of the book is updated for Python 3.6

Data Mining Editorial Review

Data Science From Scratch 2e First Principles With Python is a comprehensive resource for those looking to deepen their understanding of data science using Python. The book, published by O'Reilly on 30 April 2019, covers fundamental concepts with a solid balance of mathematical insights and coding examples, making it suitable for individuals with a foundational knowledge of Python. However, the complexity of some sections may be challenging for complete beginners, as indicated in reviews. It emphasizes applying learned principles to data sets rather than simply serving as a tutorial, making it ideal for early-stage data scientists seeking to enhance practical skills.

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Avantages

  • Comprehensive coverage of data science concepts
  • Clear explanations and code examples
  • Updated for Python 3
  • Ideal for early-stage data scientists
  • Emphasizes practical application with datasets

Les inconvénients

  • Complexity may be challenging for complete beginners

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Caractéristiques et avantages

  • Master not only the tools, but also understand the principles of data science
  • Learn Python, linear algebra, statistics, and probability
  • Explore machine learning models and techniques
  • Get updated material on deep learning and natural language processing

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