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by Andre Ye
Modern Deep Learning Design and Application Development: Versatile Tools to Solve Deep Learning Problems
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Front Matter
1. A Deep Dive into Keras
2. Pretraining Strategies and Transfer Learning
3. The Versatility of Autoencoders
4. Model Compression for Practical Deployment
5. Automating Model Design with Meta-optimization
6. Successful Neural Network Architecture Design
7. Reframing Difficult Deep Learning Problems
Back Matter
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Front Matter
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