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Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition
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Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition
Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation.
Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition
商品＃: 92437620

Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition

商品＃: 92437620

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Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation.
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Shop Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition online at a best price in Taiwan. 1804614289
Item Weight1.5 lbs (680 grams)

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Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis 1st Edition

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  • 問題: Is previous knowledge of statistics required to read this book?

    Answer: No, previous knowledge of statistics is not required but some experience with Python is helpful.
  • 問題: What statistical models will I learn about in this book?

    Answer: You will learn about regression, classification, time series analysis, and survival analysis.
  • 問題: Will I get practical experience while reading this book?

    Answer: Yes, the book provides practical guidance and illustrative examples for immediate implementation.

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特色和優勢

  • Gain expertise in identifying and modeling patterns for success.
  • Explore key statistical concepts with essential Python libraries.
  • Build models on real-world data sets for practical solutions.
  • No prior statistics knowledge needed; basic Python experience recommended.
  • Learn regression, classification, time series, and survival analysis.
  • Achieve fluency in statistical modeling for informed decision-making.

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