に同じ書籍を注文されています。
再度ご注文されますか?




Applied Supervised Learning with R P 502 p. 19

Applied Supervised Learning with R P 502 p. 19

著者:Moolayil, Jojo/Ramasubramanian, Karthik


【重要事項説明】

1.手配先によって価格が異なります。
2.納期遅延や入手不能となる場合がございます。
3.海外のクリスマス休暇等、お正月等の長期休暇時期の発注は、納期遅延となる場合がございます。
4.天候(国内・海外)により空港の発着・貨物受入不能の発生により納期遅延となる場合がございます。
5.複数冊数のご注文の場合、分納となる場合がございます。
6.美品のご指定は承りかねます。

手配先:海外仕入UK他
  • 現地価格:£35.99
  • お届けまでの予想日数: 6週間~7週間
  • 在庫数:在庫なし
  • 組合員価格:¥8,394 (税込)
手配先:海外仕入USA
  • 現地価格:$48.99
  • お届けまでの予想日数: 2週間~3週間
  • 在庫数:62
  • 組合員価格:¥8,918 (税込)
手配先:海外仕入UK他
  • 現地価格:€56.4
  • お届けまでの予想日数: 3週間~4週間
  • 在庫数:1
  • 組合員価格:¥11,111 (税込)

内容の説明

Explore supervised machine learning with R by studying popular real-world uses cases such as object detection in driverless cars, customer churn, and default prediction Key Features Study supervised learning algorithms by using real-world datasets Fine tune optimal parameters with hyperparameter optimization Select the best algorithm using the model evaluation framework Book DescriptionR provides excellent visualization features that are essential for exploring data before using it in automated learning. Applied Supervised Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your business needs. The book starts by helping you develop your analytical thinking to create a problem statement using business inputs and domain research. You will then learn different evaluation metrics that compare various algorithms, and later progress to using these metrics to select the best algorithm for your problem. After finalizing the algorithm you want to use, you will study the hyperparameter optimization technique to fine-tune your set of optimal parameters. To prevent you from overfitting your model, a dedicated section will even demonstrate how you can add various regularization terms. By the end of this book, you will have the advanced skills you need for modeling a supervised machine learning algorithm that precisely fulfills your business needs. What you will learn Develop analytical thinking to precisely identify a business problem Wrangle data with dplyr, tidyr, and reshape2 Visualize data with ggplot2 Validate your supervised machine learning model using k-fold Optimize hyperparameters with grid and random search, and Bayesian optimization Deploy your model on Amazon Web Services (AWS) Lambda with plumber Improve your model's performance with feature selection and dimensionality reduction Who this book is forThis book is specially designed for novice and intermediate-level data analyst

登録情報

商品コード:1030112951
出版社: Packt Publishing Ltd.
出版年月: 2019/05
ISBN-10: 1838556338
ISBN-13: 978-1-83855-633-4
出版国: イギリス
装丁: paper/Kt./br.
媒体: 冊子
ページ数: 502 p.
ジャンル: データベース



PAGE TOP