Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning
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Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning
A must-have practical reference for mastering Python data science tools.
Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning
Barang #: 87953333

Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning

85% of respondents would recommend this to a friend

Barang #: 87953333

IDR 849555

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A must-have practical reference for mastering Python data science tools.
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What Stands Out

Comprehensive Coverage
Covers essential tools like Jupyter, NumPy, and pandas, providing a thorough grounding in data science methods and applications for both beginners and experienced practitioners.
Hands-On Approach
Offers practical examples and exercises, allowing readers to apply concepts in real-time, enhancing learning and reinforcing data analysis skills effectively.
Updated Content
Second edition features updated libraries and techniques ensuring users stay relevant in the fast-evolving field of data science and machine learning.

Rincian Produk

Shop Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning online at a best price in Indonesia. 4814400632
Publisher u30aau30e9u30a4u30eau30fcu30fbu30b8u30e3u30d1u30f3
Publication date February 17, 2024
Language Japanese
Print length 576 pages
ISBN-10 4814400632
ISBN-13 978-4814400638
Item Weight 1 g
Dimensions 9.45 x 7.48 x 1.38 inches (24 x 19 x 3.5 cm)

Who Should Buy?

Suitable For
  • Data Science Beginners

    Ideal for those new to data science, offering comprehensive introductions to essential libraries and concepts.

  • Experienced Programmers

    Select programming professionals will appreciate advanced techniques for applying Python in data analysis and machine learning.

  • Academic Researchers

    Researchers seeking a practical guide for implementing data analysis tools and methodologies in their studies will benefit.

Not Suitable For
  • Absolute Beginners

    Individuals with no programming background may find the concepts and technical language challenging and difficult to comprehend.

DESKRIPSI PRODUK

Python Data Science Handbook 2nd Edition ―Jupyter, NumPy, pandas, Matplotlib, data analysis using scikit-learn, machine learning

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Jake VanderPlas Programming Editorial Review

Python Data Science Handbook 2nd Edition is a comprehensive guide published on February 17, 2024, designed for those looking to delve into data analysis using tools like Jupyter, NumPy, pandas, and Matplotlib. This handbook spans 576 pages, offering extensive insights into scikit-learn for machine learning, making it an invaluable resource for practitioners and learners alike. Written in Japanese, it serves both novice and experienced data scientists aiming to enhance their skills in data manipulation and visualization. The book’s hands-on approach is frequently highlighted, making complex concepts accessible, which greatly aids in mastering data science techniques.

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Bagikan pikiran Anda kepada pelanggan lain

Pro

  • Comprehensive coverage of key data science tools
  • Practical insights into machine learning applications
  • Hands-on approach enhances learning experience
  • Suitable for both beginners and advanced users
  • Well-organized layout for easy navigation

Kontra

  • Some readers may prefer an English version

Product Price History

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IDR 849555

Pesan sekarang dan dapatkan kira-kira pada Sunday, Oktober 11

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Fitur & Manfaat

  • Comprehensive guide covering essential Python data science tools.
  • Covers Jupyter, NumPy, pandas, Matplotlib, and scikit-learn.
  • Includes tips and convenient commands for efficient data analysis.
  • Ideal for handling data manipulation, visualization, and machine learning.
  • Great for beginners and experienced data scientists alike.
  • Always keep this invaluable resource at hand for your data projects.

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