Beginning deep learning with TensorFlow work with Keras, MNIST data sets, and advanced neural networks /

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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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Long, Liangqu (Author), Zeng, Xiangming (Author)
Format: Electronic eBook
Language:Inglés
Published: [United States] : Apress, 2022.
Subjects:
TensorFlow.
Machine learning.
Apprentissage automatique.
Machine learning
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.

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