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Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow
85% of respondents would recommend this to a friend
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What Stands Out
Product Details
- Teaches how to build practical deep learning applications for cloud, mobile, browsers, and edge devices using Python, Keras & TensorFlow
- Authors guide through transforming an idea into real-world usable applications
- Covers training, tuning, and deploying computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite
- Explores a variety of AI development projects for devices like Raspberry Pi, Jetson Nano, and Google Coral
- Offers practical tips for maximizing model accuracy, speed, debugging, and scaling to millions of users
- Features content contributed by industry experts and veterans
| Publisher | O'Reilly Media |
| Publication date | November 26, 2019 |
| Edition | 1st |
| Language | English |
| Print length | 620 pages |
| ISBN-10 | 149203486X |
| ISBN-13 | 978-1492034865 |
| Item Weight | 2.2 pounds (1 kg) |
| Dimensions | 7 x 1.25 x 9 inches (17.8 x 3.2 x 22.9 cm) |
Who Should Buy?
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Aspiring Data Scientists
Ideal for those wanting hands-on projects to apply machine learning concepts practically using Python and TensorFlow.
-
AI Developers
Perfect for developers looking to implement deep learning solutions in cloud, mobile, and edge computing scenarios.
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Students in AI
Beneficial for students seeking practical applications of theoretical AI knowledge in real-world scenarios.
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Beginners in Programming
Not suitable for users without a programming background, as it requires basic knowledge of Python.
Product Description
Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow
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Intelligence & Semantics Editorial Review
Practical Deep Learning for Cloud, Mobile, and Edge is a highly recommended book for AI practitioners. It provides practical knowledge and insights for building real-world AI and computer-vision projects. The book covers a wide range of topics, from theoretical concepts to the process of building and scaling practical applications. It also includes best practices, checklists, and case studies. The content is comprehensive, covering TensorFlow, Keras, CoreML, and cloud concepts for Google Cloud, AWS, and Azure. Overall, this book offers a different approach to AI than most online courses and is a valuable resource for both beginners and experienced professionals.
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Pros
- Practical knowledge and insights for building real-world AI and computer-vision projects
- Covers a wide range of topics, including theoretical concepts, best practices, checklists, and case studies
- Comprehensive coverage of TensorFlow, Keras, CoreML, and cloud concepts for major platforms
- Suitable for both beginners and experienced professionals
Cons
- Outdated and lacking outside common knowledge
Product Price History
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Features & Benefits
- Step-by-step guide for building practical deep learning applications.
- Train, tune, and deploy computer vision models.
- Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral.
- Explore fun projects and 40+ industry case studies.
- Learn transfer learning to train models in minutes.
- Discover practical tips for maximizing model accuracy, debugging, and scaling.
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