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Lecture 6 | Training Neural Networks I
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Classroom Contents
Stanford University CS231n, Spring 2017
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- 1 Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition
- 2 Lecture 2 | Image Classification
- 3 Lecture 3 | Loss Functions and Optimization
- 4 Lecture 4 | Introduction to Neural Networks
- 5 Lecture 5 | Convolutional Neural Networks
- 6 Lecture 6 | Training Neural Networks I
- 7 Lecture 7 | Training Neural Networks II
- 8 Lecture 8 | Deep Learning Software
- 9 Lecture 9 | CNN Architectures
- 10 Lecture 10 | Recurrent Neural Networks
- 11 Lecture 11 | Detection and Segmentation
- 12 Lecture 12 | Visualizing and Understanding
- 13 Lecture 13 | Generative Models
- 14 Lecture 14 | Deep Reinforcement Learning
- 15 Lecture 15 | Efficient Methods and Hardware for Deep Learning
- 16 Lecture 16 | Adversarial Examples and Adversarial Training
