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课程大纲
介绍
- AdaBoost 特点和优势概述
- 了解集成学习方法
开始
- 设置库(Numpy、Pandas、Matplotlib 等)
- 导入或加载数据集
使用 Python 构建 AdaBoost 模型
- 准备用于训练的数据集
- 使用 AdaBoostClassifier 创建实例
- 训练数据模型
- 计算和评估测试数据
使用超参数
- 探索 AdaBoost 中的超参数
- 设置值和训练模型
- 修改超参数以提高性能
最佳实践和故障排除提示
摘要和后续步骤
要求
- 了解机器学习概念
- Python 编程经验
观众
- 数据科学家
- 软件工程师
14 小时
客户评论 (3)
The details and the presentation style.
Cristian Mititean - Accenture Industrial SS
课程 - Azure Machine Learning (AML)
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
课程 - Artificial Neural Networks, Machine Learning, Deep Thinking
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete