May 2024
Intermediate to advanced
173 pages
2h 22m
Chinese
Overview
使用无监督学习建立自动化的预测和分类模型
Key Features
- 结合R语言介绍深度学习软件包H2O
- 由实际案例来讲解R语言深度学习模型
- 将R语言和深度学习模型或深度神经网络结合起来，解决实际的应用需求
Book Description
深度学习是机器学习的一个分支，其基础是一组试图使用模型架构建立高水平抽象模型的算法。本书结合R语言介绍深度学习软件包H2O，帮助读者理解深度学习的概念。本书从在R中设置可获取的重要深度学习包开始，接着转向建立神经网络、预测和深度预测等模型，所有这些模型都由实际案例的辅助来实现。成功安装了H2O软件包后，你将学习预测算法。随后本书会解释诸如过拟合数据、异常数据以及深度预测模型等概念。最后，本书会介绍设计调参和优化模型的概念。
本书适合那些胸怀大志的数据科学家，他们精通R语言数据科学概念，并希望可以使用R中的包进一步探索深度学习范式。读者需要对R语言具备基础的理解，并熟悉统计算法和机器学习技术。
What you will learn
- 建立R包H2O训练深度学习模型；
- 理解深度学习模型背后的核心概念；
- 使用自动编码器识别异常数据或离群点；
- 使用深度神经网络自动化地预测或分类数据；
- 使用正则化建立泛化模型，避免数据的过拟合。
Who this book is for
机器学习、深度学习、人工智能等相关领域的读者，高校计算机专业的学生。
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