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26355130
Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics
98% of respondents would recommend this to a friend
товар №:
26355130
KZT 75447
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What Stands Out
Comprehensive Curriculum
Covers a wide range of machine learning applications in signal processing, equipping learners with extensive knowledge in data science, algorithms, and computational statistics.
Real-World Applications
Focuses on practical use cases, enabling professionals to effectively solve signal processing problems using advanced machine learning techniques that enhance their productivity.
Expert Contributions
Written by seasoned experts in the field, ensuring high-quality insights and cutting-edge research that inform best practices in applying machine learning to data analysis.
Информация о продукте
| Publisher | Oxford University Press |
| Publication date | October 13, 2019 |
| Language | English |
| Print length | 384 pages |
| ISBN-10 | 0198714939 |
| ISBN-13 | 978-0198714934 |
| Item Weight | 2.15 pounds (980 grams) |
| Dimensions | 9.7 x 0.9 x 7.5 inches (24.6 x 2.3 x 19.1 cm) |
Who Should Buy?
-
Data Scientists
This book provides essential techniques and algorithms for data scientists looking to apply machine learning in signal processing.
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Academics and Researchers
Research professionals will benefit from the comprehensive insights into data science and computational statistics relevant to their work.
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Graduate Students
Graduate students in fields like engineering or computer science can gain foundational knowledge in ML applications for signal processing.
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Beginners in Programming
Newcomers to programming may struggle due to the book's technical depth, requiring basic knowledge of coding for comprehension.
ОПИСАНИЕ ТОВАРА
Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics
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Intelligence & Semantics Editorial Review
The book 'Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics' provides a comprehensive guide for understanding the concepts and techniques of machine learning as applied to signal processing. It covers a wide range of topics including data preprocessing, feature extraction, model selection, and evaluation. The book is well-written and offers detailed explanations of complex concepts, making it suitable for both beginners and experienced researchers in the field. The author presents practical examples and code snippets to illustrate the implementation of the algorithms. Overall, this book is a valuable resource for anyone interested in applying machine learning to signal processing.
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Плюсы
- Comprehensive guide covering various aspects of machine learning for signal processing
- Detailed explanations of complex concepts
- Practical examples and code snippets for implementation
Минусы
- None mentioned
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