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Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
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After reading this book you will be able to apply image processing techniques and make machine learning models for customized application.
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產品詳情
| Publisher | Apress |
| Publication date | February 27, 2019 |
| Edition | First Edition |
| Language | English |
| Print length | 184 pages |
| ISBN-10 | 1484241487 |
| ISBN-13 | 978-1484241486 |
| Item Weight | 9.6 ounces (272.16 grams) |
| Dimensions | 6.1 x 0.43 x 9.25 inches (15.5 x 1.1 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
This product provides foundational knowledge in machine learning and image processing specifically for aspiring professionals.
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Python Developers
Developers looking to implement facial and object recognition will find practical examples and guidance using Python.
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Academic Students
Students studying computer science or AI can benefit from structured insights into machine learning applications.
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Beginner Programmers
Those without programming knowledge may struggle with the concepts presented in this technical machine learning book.
產品描述
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
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Intelligence & Semantics Editorial Review
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python offers a primer on image processing algorithms but falls short in delivering comprehensive machine learning insights. Readers report that the material includes deprecated code and numerous erratas, making the learning process frustrating. The author provides helper modules that are not included in the book or its messy GitHub repository, leaving students without necessary resources. Although the book boasts good print quality, most readers suggest there are far better online alternatives for mastering the content offered in this text.
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優點
- Good print quality
- Covers basic image processing concepts
- Useful for initial exploration of ML
- Compact format for quick reference
- Includes foundational Python programming
缺點
- Begins with unnecessary basics for an advanced topic series
Product Price History
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特色和優勢
- Learn core image processing algorithms with Python.
- Explore the powerful OpenCV library for image processing.
- Understand advanced machine learning and deep learning methods.
- Apply techniques to real-life projects for practical application.
- Get hands-on experience with TensorFlow, scikit-learn, and NumPy.
- Designed for data scientists and software developers interested in computer vision.
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