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Barnes and Noble

Algorithms for Efficient Learning Systems

Current price: $63.72
Algorithms for Efficient Learning Systems
Algorithms for Efficient Learning Systems

Barnes and Noble

Algorithms for Efficient Learning Systems

Current price: $63.72
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In the last few decades, we have been witnessing an information revolution that can be traced back to the invention of integrated circuits and computer chips. The widespread use of electronic devices and computing resources has tremendously increased the rate at which we generate, gather and store data in every fields of science, business and engineering. Machine learning takes center stage in our quest for analyzing this vast amount of data and extracting latent knowledge from it. However, as the datasets grow, increased running time and memory constraints may become prohibitive. Additionally, real-world data can have noise and imbalanced class distribution, which adversely affect the generalization accuracy of learning algorithms. In order to cope with these challenges, science in the 21st century requires a different set of computational techniques and algorithms. This book presents methodologies that address these issues with the goal of improving scalability, computational and data efficiency and generalization performance of machine learning algorithms in the context of online and active learning with a particular focus on Support Vector Machines.

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Barnes & Noble does business -- big business -- by the book. As the #1 bookseller in the US, it operates about 720 Barnes & Noble superstores (selling books, music, movies, and gifts) throughout all 50 US states and Washington, DC. The stores are typically 10,000 to 60,000 sq. ft. and stock between 60,000 and 200,000 book titles. Many of its locations contain Starbucks cafes, as well as music departments that carry more than 30,000 titles.

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