Name: Machine Learning with Julia. An Algorithmic Exploration
SKU: 64806170
Price: 73.62 EUR
Availability: InStock
Author: Jeremiah D. Deng

portada Machine Learning with Julia. An Algorithmic Exploration

Machine Learning with Julia. An Algorithmic Exploration

Type

Physical Book

Publisher

Springer Nature Switzerland AG

Author

Jeremiah D. Deng

Collection

Machine Learning: Foundations, Methodologies, and Applications

Year

2025

Pages

418

Format

Hardcover

Dimensions

24x16.8 cm

ISBN13

9789819696888

Machine Learning with Julia. An Algorithmic Exploration

Jeremiah D. Deng (Author) · Springer Nature Switzerland AG · Hardcover

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Synopsis "Machine Learning with Julia. An Algorithmic Exploration"

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.