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Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition
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UYU 2864
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Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras.
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What Stands Out
Detalles de producto
- Learn deep learning and machine learning fundamentals with clear explanations and extensive code samples
- Implement graph neural networks, transformers, and joint and contrastive learning using TensorFlow and Keras
- Explore cutting-edge machine and deep learning techniques for cloud, mobile, and large production environments
- Understand the latest TensorFlow 2.x features, intuitive APIs based on Keras, and flexible model building on any platform
- Create and deploy neural networks with TensorFlow, covering popular algorithms such as CNNs, GANs, RNNs, NLP, and GNNs
- Target audience includes Python developers and data scientists aiming to build machine learning and deep learning systems
| Publisher | Packt Publishing |
| Publication date | October 6, 2022 |
| Edition | 3rd ed. |
| Language | English |
| Print length | 698 pages |
| ISBN-10 | 1803232919 |
| ISBN-13 | 978-1803232911 |
| Item Weight | 2.6 pounds (1.18 kg) |
| Dimensions | 7.5 x 1.58 x 9.25 inches (19.1 x 4 x 23.5 cm) |
Who Should Buy?
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Aspiring Data Scientists
Ideal for beginners seeking to learn deep learning fundamentals using TensorFlow and Keras effectively.
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Machine Learning Practitioners
Beneficial for professionals wanting to expand their knowledge in deep learning applications and model deployment.
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Academic Researchers
Useful for academics looking to implement and experiment with various deep learning models in research projects.
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Complete Beginners
Those with no programming or mathematical background might struggle to grasp advanced concepts quickly.
DESCRIPCIÓN DEL PRODUCTO
Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition
About This Item
Explore the fascinating world of deep learning with the comprehensive "Deep Learning with TensorFlow and Keras" 3rd Edition. Whether you're a beginner or an experienced practitioner, this book serves as an invaluable resource for building and deploying supervised, unsupervised, deep, and reinforcement learning models. This edition provides practical guidance, tutorials, and in-depth discussions on advanced techniques, making it a must-have for anyone delving into TensorFlow and Keras.
Elevate your understanding and mastery of deep learning models with this essential textbook.
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Expert Systems Editorial Review
The "Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition" offers a comprehensive overview of machine learning methods but is marred by numerous typos throughout the content, specifically in equations and model results. The poor print quality of the book and its sheer weight make handling it cumbersome, prompting the suggestion to divide it into multiple volumes. Furthermore, the book assumes a pre-existing familiarity with neural networks, forgoing detailed explanations of concepts and resorting to complex glossaries without sufficient background information. However, the extensive code samples and examples are lauded as invaluable resources for learning deep learning systems, particularly for individuals new to the field. While the book's thorough coverage of machine and deep learning concepts is appreciated, the lack of detail and vague explanations have been critiqued. **
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ventajas
- Offers a wide array of machine learning methods
- Extensive code samples and examples
- Thorough coverage of machine and deep learning concepts
- A valuable resource for individuals new to the field
Contras
- Littered with typos, particularly in equations and model results
Product Price History
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UYU 2864
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características y beneficios
- Learn neural networks and deep learning techniques
- Practical examples for the cloud, mobile, and large production environments
- Uses latest TF 2.0 features and libraries
- Covers GNNs, transformers, CNNs, RNNs and NLP
- Suitable for Python developers and data scientists
- No prior TF knowledge required
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