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170323720
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
84% of respondents would recommend this to a friend
Item #:
170323720
SAR 119
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What Stands Out
Hands-On Learning
Engages readers with practical Python examples, reinforcing Bayesian statistics concepts through real-world applications and interactive elements.
Modern Approach
Covers contemporary Bayesian techniques and tools, making it suitable for both beginners and those familiar with statistics who seek to update their knowledge.
Comprehensive Resource
Serves as a thorough guide to Bayesian statistics, integrating theory with coding practices to enhance understanding and applicability in various fields.
Product Details
- 機械学習エンジニア必見! ベイズ統計の基礎からベイズ統計モデリングまでPythonプログラムをもとに丁寧に解説! 【本書の内容】ベイズ統計の基礎知識からベイズ統計モデリングまで、Pythonのプログラムをもとにわかりやすく解説した書籍です。前半ではベイズ統計の理解に必要な確率の説明からはじまり、ベイズ統計学、ベイズの定理、ベイズ推定の基本事項をわかりやすく解説。後半では線形モデルを例題として、MCMC法を用いたモデルの推定方法について解説します。【本書で扱うベイズの定理について】事後分布を求める際に問題となる、ベイズの定理の積分計算を回避する方法を2つ紹介します。1つは、共役事前分布によって事後分布の解析解を求める方法です。そしてもう1つは、MCMC法を使用することで数値計算によって事後分布を推定する方法です。MCMC法はPythonのライブラリのPyMC3を用いて手軽に実践することができます。【本書の扱うベイズ統計の範囲】・確率の基本・ベイズの定理・ベイズ推定・MCMC法:マルコフ連鎖モンテカルロ法・線形モデル・一般化線形モデル【対象読者】・ベイズ統計モデリングをこれから学ぼうとされる方・ベイズ統計モデリングの基礎知識が少ない機械学習エンジニア【著者プロフィール】かくあき学生時代から数値解析を中心にPython,Matlab,Fortran,C,LISPなどのプログラミング言語を利用している。Pythonの普及の一助となるべく、Udemyで講座を公開。Kindle Direct Publishingで電子書籍を出版するなど、情報発信を行う。著書に『現場で使える! Python科学技術計算入門』(翔泳社)がある。
| Publisher | 翔泳社 |
| Publication date | August 5, 2021 |
| Language | Japanese |
| Print length | 256 pages |
| ISBN-10 | 4798168645 |
| ISBN-13 | 978-4798168647 |
| Item Weight | 340 g |
| Dimensions | 5.91 x 0.63 x 8.35 inches (15 x 1.6 x 21.2 cm) |
| Part of series | AI & TECHNOLOGY |
Who Should Buy?
-
Statistics Students
Ideal for students seeking a practical approach to Bayesian statistics using Python for hands-on learning.
-
Data Scientists
Beneficial for data scientists who want to deepen their understanding of Bayesian methods through practical implementation.
-
Educators
Great resource for educators looking to incorporate real-world applications of Bayesian statistics into their curriculum.
-
Beginners in Statistics
Not suitable for those without a foundational knowledge of statistics, as it may overwhelm them.
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かくあき Format: Tankobon Softcover Probability & Statistics Editorial Review
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 offers a practical approach to Bayesian statistics with Python programming. Published by 笠井社 in August 2021, this 256-page book is designed in Japanese, making it accessible to a wide audience interested in AI and technology. It also serves as part of the AI & TECHNOLOGY series, providing an excellent foundation for learners looking to deepen their understanding of statistical methods. Readers appreciate its clarity and hands-on examples that bolster comprehension of complex concepts.
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Pros
- Clear explanations of Bayesian statistics
- Hands-on examples enhance learning
- Suitable for beginners in statistics
- Part of a popular AI & TECHNOLOGY series
- Well-structured with practical applications
Cons
- May require basic Python knowledge
Product Price History
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Features & Benefits
- Comprehensive guide to Bayesian statistics tailored for machine learning engineers.
- Explains Bayesian concepts from fundamentals to modeling.
- Hands-on examples using Python, specifically with the PyMC3 library.
- Covers crucial topics such as Bayes' theorem and MCMC methods.
- Ideal for beginners and those seeking to enhance their statistical modeling skills.
- Structured for ease of understanding and practical application.
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