Generative Adversarial Networks in Practice

1. Introduction

2. Data Preprocessing

3. Model Evaluation

4. TensorFlow and Keras Fundamentals

5. Artificial Neural Networks Fundamentals and Architectures

6. Deep Neural Networks (DNNs) Fundamentals and Architectures

7. Generative Adversarial Networks (GANs) Fundamentals and Architectures

8. Deep Convolutional Generative Adversarial Networks (DCGANs)

9. Conditional Generative Adversarial Network (cGAN)

10. Cycle Generative Adversarial Network (CycleGAN)

11. Semi-Supervised Generative Adversarial Network (SGAN)

12. Least Squares Generative Adversarial Network (LSGAN)

13. Wasserstein Generative Adversarial Network (WGAN)

14. Generative Adversarial Networks (GANs) for Images

15. Generative Adversarial Networks (GANs) for Voice, Music, and Song

Appendix

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• Bases de Dados
• Aprendizagem mecânica
• As redes neurais e sistemas nebulosos
• Engenharia do controlo automático

deep learning models;adversarial training;neural network evaluation;image synthesis techniques;voice data generation;TensorFlow Keras implementation;practical GAN coding examples