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Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis - Helion

Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis
ebook
Autor: Huy Hoang Nguyen, Paul N Adams, Stuart J Miller
Tytuł oryginału: Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis
ISBN: 9781804612156
stron: 420, Format: ebook
Data wydania: 2023-08-31
Księgarnia: Helion

Cena książki: 125,10 zł (poprzednio: 139,00 zł)
Oszczędzasz: 10% (-13,90 zł)

Dodaj do koszyka Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis

The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. 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.

This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you’ll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you’ll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more.

By the end of this book, you’ll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis.

Dodaj do koszyka Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis

 

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Dodaj do koszyka Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis

Spis treści

Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis eBook -- spis treści

  • 1. Sampling and Generalization
  • 2. Distributions of Data
  • 3. Hypothesis Testing
  • 4. Parametric Tests
  • 5. Non-Parametric Tests
  • 6. Linear Regression
  • 7. More Discussion on Model Selection & Regularization
  • 8. Logistic Regression
  • 9. Discriminant Analysis
  • 10. Introduction to Time Series
  • 11. ARIMA Models
  • 12. Multivariate Time Series Methods
  • 13. Time to Event variables - An introduction
  • 14. Models with Survival Responses

Dodaj do koszyka Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis

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