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課程簡介
- 反向支柱,模組化模型
- Logsum 模組
- RBF凈值
- MAP/MLE 丟失
- 參數空間變換
- 卷積模組
- 基於梯度的學習
- 用於推理的能量
- 學習目標
- PCA、NLL
- 潛在變數模型
- 概率 LVM
- 損失函數
- 手寫識別
最低要求
在基礎機器學習方面打下良好的基礎。任何語言的程式設計技能(最好是 Python/R)。
21 時間:
客戶評論 (4)
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Course - Introduction to Deep Learning
The deep knowledge of the trainer about the topic.
Sebastian Görg
Course - Introduction to Deep Learning
I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
Radek
Course - Introduction to Deep Learning
Exercises after each topic were really helpful, despite there were too complicated at the end. In general, the presented material was very interesting and involving! Exercises with image recognition were great.