最新机器学习入门教材-Python for Probability,Statistics, and Machine Learning Third Edition

原创 已于 2024-06-25 14:46:05 修改 · 1k 阅读 · 3 ·
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于 2024-06-25 14:43:58 首次发布

这本书介绍了使用Python语言进行概率、统计和机器学习的基础知识和应用。这本书更新到了Python 3.8+版本，并包含大量实用的代码示例和图形可视化，以帮助读者理解和应用这些概念。书中涵盖了从Python的安装与设置，到科学计算库（如Numpy、Scipy、Pandas等）的使用，再到概率与统计理论、机器学习算法及其实现的广泛内容。

书本目录

  1. Getting Started with Scientific Python

    • Installation and Setup
    • Numpy
    • Matplotlib
    • IPython
    • Jupyter Notebook
    • Scipy
    • Pandas
    • Sympy
    • Xarray for High Dimensional Dataframes
    • Interfacing with Compiled Libraries
    • Integrated Development Environments
    • Quick Guide to Performance and Parallel Programming
    • Other Resources

  2. Probability

    • Introduction
    • Understanding Probability Density
    • Random Variables
    • Continuous Random Variables
    • Transformation of Variables Beyond Calculus
    • Independent Random Variables
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Python for Probability Statistics and Machine Learning
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This book will teach you the fundamental concepts that underpin probability and statistics and illustrates how they relate to machine learning via the Python language and its powerful extensions. This is not a good first book in any of these topics because we assume that you already had a decent undergraduate-level introduction to probability and statistics. Furthermore, we also assume that you have a good grasp of the basic mechanics of the Python language itself. Having said that, this book is appropriate if you have this basic background and want to learn how to use the scientific Python toolchain to investigate these topics. On the other hand, if you are comfortable with Python, perhaps through working in another scientific field, then this book will teach you the fundamentals of probability and statistics and how to use these ideas to interpret machine learning methods. Likewise, if you are a practicing engineer using a commercial package (e.g., Matlab, IDL), then you will learn how to effectively use the scientific Python toolchain by reviewing concepts with which you are already familiar.
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