课程大纲
介绍
- RAPIDS 功能和组件概述
- GPU 计算概念
开始
- 安装 RAPIDS
- cuDF、cUML 和 Dask
- 基元、算法和 API
管理和训练数据
- 数据准备和 ETL
- 使用 XGBoost 创建训练集
- 测试训练模型
- 使用 CuPy 数组
- 使用 Apache Arrow 数据框
可视化和部署模型
- 使用 cuGraph 进行图形分析
- 使用 Dask 实现 Multi-GPU
- 使用 cuXfilter 创建交互式仪表板
- 推理和预测示例
故障 排除
摘要和后续步骤
要求
- 熟悉 CUDA
- Python 编程经验
观众
- 数据科学家
- 开发 人员
客户评论 (5)
示例/练习完全适合我们的领域
Luc - CS Group
课程 - Scaling Data Analysis with Python and Dask
机器翻译
培训师非常乐意回答我所做的所有问题
Caterina - Stamtech
课程 - Developing APIs with Python and FastAPI
机器翻译
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
课程 - Build REST APIs with Python and Flask
传授培训师的实践知识和经验。
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
课程 - GUI Programming with Python and PyQt
机器翻译
As I was the only participant the training could be adapted to my needs.