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Find a path to becoming a Pattern Evaluation. Learn more at:
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Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Pattern Evaluation.
Classic in the field of pattern recognition and provides a comprehensive overview of pattern classification techniques.
Covers the theoretical foundations of machine learning for pattern recognition and provides a thorough understanding of the underlying concepts.
Focuses on modern pattern evaluation techniques and provides a comprehensive overview of pattern recognition and machine learning.
Covers pattern recognition techniques for image and speech analysis, providing a comprehensive overview of the field.
Covers pattern evaluation techniques for natural language processing (NLP), providing a thorough treatment of the field.
Covers pattern recognition techniques for medical imaging, providing a thorough treatment of the field.
Covers pattern recognition techniques for computer vision, providing a thorough treatment of the field.
Covers pattern recognition techniques for data mining, providing a thorough treatment of the field.
Provides a broad overview of pattern recognition and machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a statistical approach to pattern recognition and covers topics such as Bayesian inference, discriminant analysis, and clustering.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/5nqrq0/pattern
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