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- Hands-On Machine Learning with C++: Build, tr...
Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines
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€ 72
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This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data.
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What Stands Out
Produkto Aprašymas
- Learn to implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with real-world examples and datasets
- Understand data processing, performance measuring, and model selection using various C++ libraries
- Gain practical experience in deploying machine learning models to work on mobile and embedded devices
- Explore techniques including product recommendations, ensemble learning, and anomaly detection using modern C++ libraries
- Discover how to handle production and deployment challenges on mobile and cloud platforms
- Develop the skills to use C++ to build powerful machine learning systems and proficient understanding of C++ language is required
| Publisher | Packt Publishing |
| Publication date | May 15, 2020 |
| Language | English |
| Print length | 530 pages |
| ISBN-10 | 1789955335 |
| ISBN-13 | 978-1789955330 |
| Item Weight | 2.21 pounds (1 kg) |
| Dimensions | 7.5 x 1.2 x 9.25 inches (19.1 x 3 x 23.5 cm) |
Who Should Buy?
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Beginner Developers
New developers can learn machine learning concepts effectively through practical examples and hands-on projects with C++.
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Data Scientists
Data scientists looking to implement machine learning models in production will benefit from end-to-end project coverage.
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C++ Enthusiasts
C++ programmers eager to apply their skills to machine learning will find this book particularly useful and engaging.
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Non-Technical Users
Users without a programming background may struggle with the technical content and programming requirements of the book.
PRODUKTO APRAŠYMAS
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Natural Language Processing Editorial Review
Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines is a comprehensive guide tailored for C++ programmers looking to delve into the realm of machine learning. The author's approach combines practical examples using real csv data, which enhances the learning experience by allowing immediate application of concepts. The book focuses on essential topics such as supervised and unsupervised learning methods, and also provides advanced examples and deployment challenges. Despite the steep learning curve associated with C++17, readers find the organization and depth of content to be highly valuable for bridging the gap between traditional C++ programming and modern machine learning practices.
Customer Reviews & Ratings
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5 žvaigždė
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4 žvaigždė
32%
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3 žvaigždė
4%
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2 žvaigždė
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Argumentai
- Includes practical, real-world coding examples
- Covers essential supervised and unsupervised learning
- Well-organized with useful further reading sections
- Allows C++ developers to leverage ML techniques
- Explains deployment challenges effectively
Minusai
- A learning curve may arise from C++17 code usage
Product Price History
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Savybės ir privalumai
- Learn the fundamentals of machine learning using C++ libraries.
- Implement supervised and unsupervised ML algorithms through real-world examples.
- Tune and optimize models for different use cases, measure performance.
- Handle production and deployment challenges on mobile and cloud platforms.
- Use C++ to build powerful ML systems.
- Suitable for beginners and professionals with working knowledge of C++.
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