| 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 | | | 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 |
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发表于 2025-3-21 19:49:40
