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课程大纲
介绍
- Apache MXNet 与 PyTorch
Deep Learning 原则和 Deep Learning 生态系统
- 张量、多层感知器、卷积 Neural Networks 和递归 Neural Networks
- 计算机视觉与自然语言处理
Apache MXNet 功能和体系结构概述
- Apache MXNet 组件
- Gluon API 接口
- GPU 和模型并行性概述
- 符号式和命令式编程
设置
- 选择部署环境(本地部署、公有云等)
- 安装 Apache MXNet
使用数据
- 读入数据
- 验证数据
- 操作数据
开发 Deep Learning 模型
- 创建模型
- 训练模型
- 优化模型
部署模型
- 使用预训练模型进行预测
- 将模型集成到应用程序中
MXNet 安全最佳实践
故障 排除
总结和结论
要求
- 了解机器学习原理
- Python 编程经验
观众
- 数据科学家
21 小时
客户评论 (4)
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 structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
课程 - Introduction to Deep Learning
I was benefit from the passion to teach and focusing on making thing sensible.
Zaher Sharifi - GOSI
课程 - Advanced Deep Learning
examples based on our data