{ "item_title" : "Machine Learning with Julia", "item_author" : [" Jeremiah D. Deng "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/81/969/688/9819696887_b.jpg", "price_data" : { "retail_price" : "79.99", "online_price" : "79.99", "our_price" : "79.99", "club_price" : "79.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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