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Deep learning using Keras : a complete and compact guide for beginners /
Learn deep learning from scratch using Python and Keras. The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Birmingham, United Kingdom] :
Packt Publishing,
[2021]
|
| Edición: | [First edition]. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 245 | 0 | 0 | |a Deep learning using Keras : |b a complete and compact guide for beginners / |c Abhilash Nelson. |
| 250 | |a [First edition]. | ||
| 264 | 1 | |a [Birmingham, United Kingdom] : |b Packt Publishing, |c [2021] | |
| 300 | |a 1 online resource (1 video file (9 hr., 37 min.)) : |b sound, color. | ||
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| 500 | |a "Updated in October 2021." | ||
| 511 | 0 | |a Abhilash Nelson, presenter. | |
| 520 | |a Learn deep learning from scratch using Python and Keras. The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features from data without human intervention. That makes deep learning the base of all future self-intelligent systems. This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries—Theano and TensorFlow—and the API for dealing with these called Keras. Then, before we jump into deep learning, we will have an elaborate theory session about the basic structure of artificial neuron and neural networks, and about activation functions, loss functions, and optimizers. | ||
| 588 | 0 | |a Online resource; title from title details screen (O’Reilly, viewed March 7, 2022). | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 2 | |a Neural Networks, Computer | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
| 650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
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| 655 | 7 | |a Nonfiction films. |2 lcgft | |
| 655 | 7 | |a Internet videos. |2 lcgft | |
| 655 | 7 | |a Films de formation. |2 rvmgf | |
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| 700 | 1 | |a Nelson, Abhilash, |e presenter. | |
| 710 | 2 | |a Packt Publishing, |e publisher. | |
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