Course Code: radvml
Duration: 21 hours
Prerequisites:
  • R 编程经验
  • 了解机器学习概念
Overview:

在这个由讲师指导的现场培训中，参与者将学习 Machine Learning with R 的高级技术，同时逐步创建真实世界的应用程式。

在本次培训结束时，参与者将能够：

  • 了解并实施无监督学习技术
  • 应用聚类和分类，根据真实数据进行预测。
  • 可视化数据以快速获得洞察、做出决策并进一步优化分析。
  • 使用超参数优化提高机器学习模型的性能。
  • 将模型投入生产，以便在更大的应用程式中使用。
  • 应用高级机器学习技术来回答涉及社交网路数据、大数据等的问题。

观众

  • 开发人员
  • 分析师
  • 数据科学家

课程形式

  • 部分讲座、部分讨论、练习和大量动手实践
Course Outline:

介绍

设置 R 开发环境

深度学习与神经网络与 Machine Learning

构建无监督学习模型

案例研究：使用现有数据预测结果

准备用于分析的测试和训练数据集

聚类数据

对数据进行分类

可视化数据

评估模型的性能

遍历模型参数

超参数调优 

将模型与实际应用程序集成

部署 Machine Learning 应用程序

故障 排除

总结和结论

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