Machine Learning with Julia
Deng, Jeremiah D.
Produktnummer:
18bdf60e37a25749428db3081f5125e4fe
| Autor: | Deng, Jeremiah D. |
|---|---|
| Themengebiete: | Julia Programming Julia book Julia for machine learning Julia language Julia machine learning deep learning with Julia machine learning with Julia reinforcement learning with Julia |
| Veröffentlichungsdatum: | 19.11.2025 |
| EAN: | 9789819696895 |
| Sprache: | Englisch |
| Seitenzahl: | 418 |
| Produktart: | Unbekannt |
| Verlag: | Springer Singapore |
| Untertitel: | An Algorithmic Exploration |
Produktinformationen "Machine Learning with Julia"
This textbook offers a comprehensive and accessible introduction to machine learning with the Julia programming language. It bridges mathematical theory and real-world practice, guiding readers through both foundational concepts and advanced algorithms. Covering topics from essential principles like Kullback–Leibler divergence and eigen-analysis to cutting-edge techniques such as deep transfer learning and differential privacy, each chapter delivers clear explanations and detailed algorithmic treatments. Sample code accompanies every major topic, enabling hands-on learning and faster implementation.By leveraging Julia’s powerful machine learning ecosystem—including libraries such as Flux.jl, MLJ.jl, and more—this book empowers readers to build robust, state-of-the-art machine learning models.Ideal for students, researchers, and professionals alike, this textbook is designed for those seeking a solid theoretical foundation in machine learning, along with deep algorithmic insight and practical problem-solving inspiration.
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