Beginning deep learning with TensorFlow work with Keras, MNIST data sets, and advanced neural networks /
Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learn...
Call Number: | Libro Electrónico |
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Main Authors: | , |
Format: | Electronic eBook |
Language: | Inglés |
Published: |
[United States] :
Apress,
2022.
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Subjects: | |
Online Access: | Texto completo (Requiere registro previo con correo institucional) |
Table of Contents:
- Chapter 1: Introduction to Artificial Intelligence
- Chapter 2. Regression
- Chapter 3. Classification
- Chapter 4. Basic Tensorflow
- Chapter 5. Advanced Tensorflow
- Chapter 6. Neural Network
- Chapter 7. Backward Propagation Algorithm
- Chapter 8. Keras Advanced API
- Chapter 9. Overfitting
- Chapter 10. Convolutional Neural Networks
- Chapter 11. Recurrent Neural Network
- Chapter 12. Autoencoder
- Chapter 13. Generative Adversarial Network (GAN)
- Chapter 14. Reinforcement Learning
- Chapter 15. Custom Dataset.