Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
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What you'll learn
This course includes
- 19.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 16 lessons • 19.5 hours of video
Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
16 lessons
• 19.5 hours
Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
16 lessons
• 19.5 hours
- Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition 57:57
- Lecture 2 | Image Classification 59:32
- Lecture 3 | Loss Functions and Optimization 01:14:40
- Lecture 4 | Introduction to Neural Networks 01:13:59
- Lecture 5 | Convolutional Neural Networks 01:08:56
- Lecture 6 | Training Neural Networks I 01:20:20
- Lecture 7 | Training Neural Networks II 01:15:30
- Lecture 8 | Deep Learning Software 01:18:07
- Lecture 9 | CNN Architectures 01:17:40
- Lecture 10 | Recurrent Neural Networks 01:13:09
- Lecture 11 | Detection and Segmentation 01:14:26
- Lecture 12 | Visualizing and Understanding 01:15:48
- Lecture 13 | Generative Models 01:17:41
- Lecture 14 | Deep Reinforcement Learning 01:04:01
- Lecture 15 | Efficient Methods and Hardware for Deep Learning 01:16:52
- Lecture 16 | Adversarial Examples and Adversarial Training 01:21:46
