Think Bayes: Bayesian Statistics in Python 2nd
Downey, Allen B.
- 出版商: O'Reilly
- 出版日期: 2021-06-22
- 定價: $1,980
- 售價: 9.5 折 $1,881
- 貴賓價: 9.0 折 $1,782
- 語言: 英文
- 頁數: 338
- 裝訂: Quality Paper - also called trade paper
- ISBN: 149208946X
- ISBN-13: 9781492089469
-
相關分類:
Python、程式語言、機率統計學 Probability-and-statistics
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相關主題
商品描述
If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems.
Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book's computational approach helps you get a solid start.
- Use your programming skills to learn and understand Bayesian statistics
- Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing
- Get started with simple examples, using coins, dice, and a bowl of cookies
- Learn computational methods for solving real-world problems
商品描述(中文翻譯)
如果你懂得如何程式設計,你就準備好學習貝葉斯統計了。這本書將教你如何使用Python程式碼解決統計問題,而不是使用數學公式,使用離散概率分佈而不是連續數學。一旦你掌握了數學,貝葉斯基礎將變得更清晰,你將開始將這些技術應用於實際問題。
貝葉斯統計方法變得越來越常見和重要,但沒有太多資源可供初學者使用。根據作者Allen Downey所教授的本科課程,這本書的計算方法將幫助你有一個堅實的開始。
- 利用你的程式設計技能學習和理解貝葉斯統計
- 處理涉及估計、預測、決策分析、證據和貝葉斯假設檢驗的問題
- 從簡單的例子入手,使用硬幣、骰子和一碗餅乾
- 學習解決實際問題的計算方法
作者簡介
Allen Downey is a Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT. He is author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.
作者簡介(中文翻譯)
Allen Downey 是奧林工程學院的計算機科學教授。他曾在韋爾斯利學院、科爾比學院和加州大學伯克利分校教授計算機科學。他擁有加州大學伯克利分校的計算機科學博士學位,以及麻省理工學院的碩士和學士學位。他是《Think Python》、《Think Bayes》、《Think DSP》以及一個名為《Probably Overthinking It》的部落格的作者。