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Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python
78% of respondents would recommend this to a friend
KZT 32460
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Learn TensorFlow 2.0 to build machine learning and deep learning models with complete examples.
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Информация о продукте
| Publisher | Apress |
| Publication date | January 5, 2020 |
| Edition | First Edition |
| Language | English |
| Print length | 180 pages |
| ISBN-10 | 1484255607 |
| ISBN-13 | 978-1484255605 |
| Item Weight | 9.6 ounces (272.16 grams) |
| Dimensions | 6.1 x 0.41 x 9.25 inches (15.5 x 1 x 23.5 cm) |
Who Should Buy?
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Beginners in AI
Ideal for those new to artificial intelligence and machine learning, providing foundational concepts and practical examples.
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Data Scientists
Useful for data scientists seeking to implement TensorFlow in their projects, enhancing their skill set effectively.
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Students in Tech
Perfect for university students studying computer science or data science, helping them grasp TensorFlow for their coursework.
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Experts in AI
Not suitable for AI experts as it covers basic concepts and may not meet advanced learning needs.
ОПИСАНИЕ ТОВАРА
Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python
Вопросы и ответы клиентов
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вопрос:
What are the prerequisites for learning TensorFlow 2.0 using this book?
отвечать: To effectively learn TensorFlow 2.0 through this book, a basic understanding of Python programming is essential since the examples and exercises are written in Python. Familiarity with fundamental machine learning concepts, including supervised and unsupervised learning, as well as neural networks, will enhance your comprehension. This foundational knowledge allows you to grasp advanced topics more quickly and integrate practical applications effectively, making the learning experience smoother. -
вопрос:
Is this book suitable for beginners in machine learning?
отвечать: Yes, 'Learn TensorFlow 2.0' is designed to be beginner-friendly while also catering to more experienced learners. It starts with foundational concepts and gradually transitions to more complex topics, ensuring that you build a solid base of understanding. With clear explanations, practical examples, and exercises, beginners can confidently follow along and apply what they've learned. This structure allows readers to progress at their own pace, fostering both skill acquisition and practical knowledge. -
вопрос:
What kind of projects can I build using this book?
отвечать: This book guides you through various projects, enabling you to create real-life applications such as image classification systems, natural language processing models, and reinforcement learning agents. Each project is designed to reinforce learning by applying theoretical knowledge to practical scenarios, showcasing TensorFlow's capabilities. By working on these projects, you can develop a portfolio that demonstrates your mastery of machine learning and deep learning techniques in TensorFlow. -
вопрос:
Are there any coding exercises included in the book?
отвечать: Absolutely! The book includes numerous coding exercises and problems at the end of each chapter. These exercises are tailored to reinforce the concepts covered and facilitate hands-on learning. Engaging in these exercises helps solidify your knowledge and offers an opportunity to apply what you've learned in real-world contexts. Moreover, working through these practical examples enhances your coding skills while deepening your understanding of TensorFlow functionalities. -
вопрос:
Does this book cover the latest features of TensorFlow 2.0?
отвечать: Yes, 'Learn TensorFlow 2.0' thoroughly covers the latest features and enhancements introduced in TensorFlow 2.0. It discusses eager execution, simplified APIs, and various new tools and libraries that streamline model building and training. By staying updated on these features, readers can leverage the full potential of TensorFlow 2.0 in their projects. Thus, you can ensure that your knowledge remains relevant and applicable in today’s fast-evolving tech landscape. -
вопрос:
How well does the book explain deep learning concepts?
отвечать: The book provides a comprehensive introduction to deep learning concepts alongside practical TensorFlow implementations. It explains core ideas such as neural networks, convolutional networks, and recurrent networks through both theoretical discussions and concrete code examples. This dual approach allows readers to grasp deep learning fundamentals while actively applying them. As a result, you will develop a strong understanding of deep learning that you can implement in real-world applications. -
вопрос:
Can I use this book for self-study, and how should I approach it?
отвечать: Yes, this book is highly suitable for self-study. To make the most of your learning experience, start by reading each chapter thoroughly before attempting the coding exercises. Take your time to understand the concepts and try modifying the code to explore different outcomes. Supplement your study with online resources and communities to address questions and share knowledge. This methodical approach will solidify your learning and foster your development skills in TensorFlow. -
вопрос:
Are there any online resources to complement the learning from this book?
отвечать: Yes, many online resources complement the learning from this book. TensorFlow’s official website offers tutorials, documentation, and a variety of community forums where you can seek assistance. Additionally, platforms like GitHub provide open-source projects relevant to the book's content, allowing you to see practical applications in action. Engaging with these resources enhances your learning by providing diverse perspectives and real-world applications of TensorFlow concepts. -
вопрос:
Is this book applicable for both academic and practical purposes?
отвечать: Definitely! 'Learn TensorFlow 2.0' bridges the gap between theoretical concepts and practical application, making it suitable for both academic and industry contexts. Students can benefit from its structured approach to learning machine learning principles, while professionals can utilize the practical projects to enhance their skills or implement solutions in their work environments. This versatility makes the book a valuable resource for varied audiences looking to deepen their understanding of TensorFlow. -
вопрос:
Where can I buy Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python First Edition?
отвечать: You can purchase 'Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python First Edition' on Ubuy in Kazakhstan. Ubuy offers a wide selection of books and ensures you have access to essential resources for your learning journey. Their streamlined online shopping experience makes it easy to find and acquire this valuable educational resource, setting you on a path to mastering TensorFlow.
Intelligence & Semantics Editorial Review
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- Comprehensive coverage of TensorFlow 2.0
- Good for beginners and intermediates
- Hands-on coding examples provided
- Clear explanations of concepts
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- Outdated information for 2023
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Особенности и преимущества
- Introduces TensorFlow 2.0 framework and major changes
- Focuses on building Supervised Machine Learning models using TensorFlow 2.0
- Demonstrates building models using custom estimators
- Explains using TensorFlow 2.0 API for image classification models
- Covers sequence predictions, saving, serving, deploying, and standardized datasets
- Provides executable scripts at Github to try out and extend examples
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