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岩波データサイエンス サポートページ 各巻に対応する内容は，上のバーの３本線「三」をクリックして左に表示されるメニューからご覧ください （トップページの内容が空白の場合も，メニューで下位の階層をクリックして頂くと内容が表示される場合があります） 新グーグル・サイトに移行しました．自動変換のため，見難くなっている部分，表示されない部分がありますが，ご容赦ください シリーズ「岩波データサイエンス」では、統計科学や機械学習など、データを扱うさまざまな分野について、多様な視点からの情報を提供することをめざします。まったくの初歩からやや高度な話までのいろいろな手法の解説、実務に役立つソフトの使い方、さらには各領域のサイエンスや応用に踏み込んだ内容まで、多彩な記事を掲載します。 装丁には蛯名優子さんの作品を使わせて頂いています。蛯名さんのホームページはこちらです。 【公式ツイッターアカウント】ツイッタ
Welcome | R for Data Science
This is the website for the first edition of “R for Data Science”, published January 2017. This book is now out-of-date and instead we recommend the 2nd edition at http://r4ds.hadley.nz/ which was published in June 2023. R4DS teaches you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this b
Intermediate Python — Python Tips 0.1 documentation
Note You can sign up to my mailing list so that you remain in sync with any major updates to this book or my future projects! Preface¶ Python is an amazing language with a strong and friendly community of programmers. However, there is a lack of documentation on what to learn after getting the basics of Python down your throat. Through this book I aim to solve this problem. I would give you bits o
HTML5 Canvas
Read it now on the O’Reilly learning platform with a 10-day free trial. O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers. No matter what platform or tools you use, the HTML5 revolution will soon change the way you build web applications, if it hasn't already. HTML5 is jam-packed with features, and there's
Home | Data Science at the Command Line
👋 Hi there! I’m Jeroen. In 2021 I wrote the second edition of Data Science at the Command Line, which you can read entirely for free here. If you find this book helpful, consider spreading the word! You could, for instance, share it on Twitter, write a review on Amazon, or star the Github repository. Much appreciated! Read Data Science at the Command Line for free Be sure to let me know if you ha
Introduction to Information Retrieval
This is the companion website for the following book. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008. You can order this book at CUP, at your local bookstore or on the internet. The best search term to use is the ISBN: 0521865719. The book aims to provide a modern approach to information retrieval from a compu
Home page for the book, "Bayesian Data Analysis"
This is the home page for the book, Bayesian Data Analysis, by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin. Here is the book in pdf form, available for download for non-commercial purposes. Teaching Bayesian data analysis Aki Vehtari's course material, including video lectures, slides, and his notes for most of the chapters. 77 best lines from my course A stu
GitHub - JWarmenhoven/ISLR-python: An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
This repository contains Python code for a selection of tables, figures and LAB sections from the first edition of the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013). For Bayesian data analysis using PyMC3, take a look at this repository. 2018-01-15: Minor updates to the repository due to changes/deprecations in several packages. T
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Meta-Analysis with R
https://blogs.microsoft.com/uploads/2018/02/The-Future-Computed_2.8.18.pdf
R Tutorial With Bayesian Statistics Using Stan | R Tutorial
Advanced Statistical Computing
ブクログ
Recipe | Café&Meal MUJI
Welcome to Text Mining with R | Text Mining with R
bookshelf
Books for self-studying time series analysis?
GitHub - dgrtwo/empirical-bayes-book: Introduction to Empirical Bayes: Examples from Baseball Statistics