| 书目名称 | Introduction to Deep Learning Using R |
| 副标题 | A Step-by-Step Guide |
| 编辑 | Taweh Beysolow II |
| 视频video | http://file.papertrans.cn/474/473603/473603.mp4 |
| 概述 | The code in this book utilizes R studio and its packages, all of which are open source, to make the learning process as simple as possible.Each chapter builds upon the knowledge of the preceding chapt |
| 图书封面 |  |
| 描述 | .Understand deep learning, the nuances of its different models, and where these models can be applied..The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. .Introduction to Deep Learning Using R. provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning and deep learning. This step-by-step guide will help you understand the disciplines so that you can apply the methodology in a variety of contexts. All examples are taught in the R statistical language, allowing students and professionals to implement these techniques using open source tools..What You‘ll Learn.Understand the intuition and mathematics that power deep learning models.Utilize various algorithms using the R programming language and its packages.Use best practices for experimental design and variable selection.Practice the methodology to approach and effectively solve problems as a data scientist.Evaluate the effectiveness of algorithmic solutions and enhance their predictive power.Who This Book I |
| 出版日期 | Book 2017 |
| 关键词 | Deep Learning; R; Single Layer Artificial Neural Networks; Deep Neural Networks; Convolutional Neural Ne |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4842-2734-3 |
| isbn_softcover | 978-1-4842-2733-6 |
| isbn_ebook | 978-1-4842-2734-3 |
| copyright | Taweh Beysolow II 2017 |
|Archiver|手机版|小黑屋|
派博传思国际
( 京公网安备110108008328)
GMT+8, 2025-8-6 23:18
发表于 2025-3-21 19:49:40
