Think Bayes: Edition 2
2021年5月 · "O'Reilly Media, Inc."
5.0star
1 則評論report
電子書
338
頁
family_home
符合資格
info
report評分和評論未經驗證 瞭解詳情
關於本電子書
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 there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. 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
評分和評論
5.0
1 則評論
關於作者
Allen Downey is a Professor of Computer Science at 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 the author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.
為這本電子書評分
歡迎提供意見。
閱讀資訊
智慧型手機與平板電腦
筆記型電腦和電腦
你可以使用電腦的網路瀏覽器聆聽你在 Google Play 購買的有聲書。
電子書閱讀器與其他裝置
如要在 Kobo 電子閱讀器這類電子書裝置上閱覽書籍，必須將檔案下載並傳輸到該裝置上。請按照說明中心的詳細操作說明，將檔案傳輸到支援的電子閱讀器上。
