Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
A must-see for machine learning engineers!
Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY
Item #: 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

Item #: 170323720

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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

Shop Pythonで動かして学ぶ! あたらしいベイズ統計の教科書 AI & TECHNOLOGY online at a best price in Singapore. 4798168645
  • 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?

Suitable For
  • 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.

Not Suitable For
  • 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

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