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

    Posted By: yoyoloit
    Building Statistical Models in Python: Develop useful models for regression, classification, time series and survival analysis

    Building Statistical Models in Python
    by Huy Hoang Nguyen, Paul N Adams, Stuart J Miller

    English | 2023 | ISBN: 1804614289 | 420 pages | True/Retail PDF EPUB | 71.12 MB




    Make data-driven, informed decisions and enhance your statistical expertise in Python by turning raw data into meaningful insights

    Purchase of the print or Kindle book includes a free PDF eBook
    Key Features

    Gain expertise in identifying and modeling patterns that generate success
    Explore the concepts with Python using important libraries such as stats models
    Learn how to build models on real-world data sets and find solutions to practical challenges

    Book Description

    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.
    What you will learn

    Explore the use of statistics to make decisions under uncertainty
    Answer questions about data using hypothesis tests
    Understand the difference between regression and classification models
    Build models with stats models in Python
    Analyze time series data and provide forecasts
    Discover Survival Analysis and the problems it can solve

    Who this book is for

    If you are looking to get started with building statistical models for your data sets, this book is for you! Building Statistical Models in Python bridges the gap between statistical theory and practical application of Python. Since you’ll take a comprehensive journey through theory and application, no previous knowledge of statistics is required, but some experience with Python will be useful.
    Table of Contents

    Sampling and Generalization
    Distributions of Data
    Hypothesis Testing
    Parametric Tests
    Non-Parametric Tests
    Linear Regression
    More Discussion on Model Selection & Regularization
    Logistic Regression
    Discriminant Analysis
    Introduction to Time Series
    ARIMA Models
    Multivariate Time Series Methods
    Time to Event variables - An introduction
    Models with Survival Responses



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