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課程簡介
介紹
- Apache MXNet 與 PyTorch
Deep Learning 原則和 Deep Learning 生態系統
- 張量、多層感知器、捲積 Neural Networks 和遞歸 Neural Networks
- 計算機視覺與自然語言處理
Apache MXNet 功能和體系結構概述
- Apache MXNet 元件
- Gluon API 介面
- GPU 和模型並行性概述
- 符號式和命令式程式設計
設置
- 選擇部署環境(本地部署、公有雲端等)
- 安裝 Apache MXNet
使用數據
- 讀入數據
- 驗證數據
- 操作數據
開發 Deep Learning 模型
- 創建模型
- 訓練模型
- 優化模型
部署模型
- 使用預訓練模型進行預測
- 將模型整合到應用程式中
MXNet 安全最佳實踐
故障排除
總結和結論
最低要求
- 了解機器學習原理
- Python 程式設計經驗
觀眾
- 數據科學家
21 時間:
客戶評論 (5)
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
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
Very flexible
Frank Ueltzhöffer
Course - Artificial Neural Networks, Machine Learning and Deep Thinking
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Course - Introduction to Deep Learning
I was benefit from the passion to teach and focusing on making thing sensible.
Zaher Sharifi - GOSI
Course - Advanced Deep Learning
examples based on our data