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课程大纲
介绍
- Random Forest 特点和优势概述
- 了解决策树和集成方法
开始
- 设置库（Numpy、Pandas、Matplotlib 等）
- Random Forests中的分类和回归
- 用例和示例
实现 Random Forest
- 准备用于训练的数据集
- 训练机器学习模型
- 评估和提高准确性
调整 Random Forest 中的超参数
- 执行交叉验证
- 随机搜索和网格搜索
- 可视化训练模型性能
- 优化超参数
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 (5)
培训师表明他对这个主题有很好的理解。
Marino - EQUS - The University of Queensland
课程 - Machine Learning with Python – 2 Days
机器翻译
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
The enthusiasm to the topic. The examples he made an he explained it very well. Sympatic. A little to detailed for beginners. For managers, it could be more abstract in fewer days. But it was designed to fit and we had a good alignment in advance.
Benedikt Chiandetti - HDI Deutschland Bancassurance Kundenservice GmbH
课程 - Machine Learning Concepts for Entrepreneurs and Managers
Convolution filter
Francesco Ferrara
课程 - Introduction to Machine Learning
The trainer was so knowledgeable and included areas I was interested in.
