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Introduction
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Classroom Contents
A Friendly Introduction to Codeless Deep Learning with KNIME Analytics Platform
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- 1 Introduction
- 2 Basic Idea
- 3 Example
- 4 New Sample
- 5 Gradient Descent
- 6 Forward Pass
- 7 Learning Rate
- 8 Important Considerations
- 9 Fully Connected Neural Network
- 10 When do Neural Network become Deep
- 11 Computer Vision
- 12 Representation
- 13 Encoding
- 14 Filters
- 15 Filter multiplication
- 16 Convolutional layer
- 17 Weight
- 18 Stride
- 19 Pooling
- 20 Network Structure
- 21 Network Architecture
- 22 Transfer Learning
- 23 KNIME Hub
- 24 Nam Community
- 25 Book Recommendation
- 26 Webinars
