Clear data science and machine learning
Clear data science and machine learning
Clear data science and machine learning
Clear data science and machine learning
Clear data science and machine learning
Clear data science and machine learning
Clear data science and machine learning
Learn the essence of exploratory data analysis and machine learning with clear insights into AI transparency.
Clear data science and machine learning
Artículo nº.: 87923793

Clear data science and machine learning

Artículo nº.: 87923793

AWG 58

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Comprehensive Insights
This hardcover edition provides thorough coverage of data science and machine learning, addressing both fundamental theories and practical applications for aspiring data professionals and students.
Expert Authorship
Authored by industry experts, it offers credible insights and best practices, making it a trusted resource for learning and mastering complex concepts in data analysis and machine learning.
Durable Format
The tankobon hardcover format ensures durability and longevity, making it an ideal addition to any study space or professional library, perfect for repeated reference and study over time.

Detalles de producto

Shop Clear data science and machine learning online at a best price in Aruba. 4764906120
  • Machine learning, which is the cornerstone of AI, has the problem of turning the process of deriving results into a black box, which is an obstacle to the practical application of AI. As a solution to this problem, it is expected to utilize ''data science'' in its original sense, which uses careful data analysis to express phenomena behind data using statistical models. By using models with understandable mechanisms in the AI brain, we can also achieve AI transparency ――, or explainable XAI! In addition to explaining statistical modeling based on the ideas of data science, this book uses R to experience typical machine learning methods. By reading this book, you can learn the essence of exploratory data analysis and machine learning.  
Publisher 近代科学社
Publication date May 29, 2020
Language Japanese
Print length 236 pages
ISBN-10 4764906120
ISBN-13 978-4764906129
Item Weight 440 g
Dimensions 9.13 x 7.13 x 0.47 inches (23.2 x 18.1 x 1.2 cm)

¿Quién debería comprarlo?

Suitable For
  • Aspiring Data Scientists

    Individuals looking to build a foundational understanding of data science will benefit from clear and practical explanations.

  • Educators and Trainers

    Teachers needing a comprehensive resource to educate students about data science and machine learning concepts will find this useful.

  • Professionals Transitioning Fields

    Industry professionals aiming to shift into data science roles will gain valuable insights and skills from this book.

Not Suitable For
  • Advanced Practitioners

    Experienced data scientists may find the book's content too basic and not aligned with their advanced learning needs.

  • Casual Readers

    Individuals not seriously engaged in data science might not find the technical material interesting or relevant to them.

  • Non-Technical Users

    Readers without a technical background may struggle with the jargon and concepts presented, limiting their comprehension.

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Preguntas y respuestas de los clientes

  • pregunta: What prior knowledge do I need to understand this book?

    responder: Basic knowledge of statistics and programming in R will enhance your experience.
  • pregunta: Is this book suitable for beginners in data science?

    responder: Yes, it is designed to help beginners grasp the fundamental concepts effectively.
  • pregunta: Will I be able to apply the concepts learned in this book in real-world scenarios?

    responder: Absolutely! The book focuses on practical applications of machine learning and data analysis.

横内大介 , 大槻健太郎 AI & Machine Learning Editorial Review

  • ubuy Aruba
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ventajas

  • Highly effective learning tool
  • User-friendly interface
  • Engaging content and activities
  • Supports various learning styles
  • Regular updates and improvements

Contras

  • Might have a small learning curve initially.

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