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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Ebook Download An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software.File Size=5318 KB. Print Length=208 pages. Simultaneous Device Usage=Up to 4 simultaneous devices, per publisher limits. Publisher=Cambridge University Press; 1 edition (March 23, 2000). Publication Date=March 23, 2000. Sold by=Amazon Digital Services LLC. Language=English. ASIN=B00AKE1PR8. Text-to-Speech=Enabled. X-Ray for Textbooks=Enabled. Word Wise=Not Enabled. Lending=Not Enabled. Enhanced Typesetting=Enabled. Amazon Best Sellers RankBioinformaticsArtificial IntelligenceAlgorithms=#1,328,795 Paid in Kindle Store (See Top 100 Paid in Kindle Store) .zg_hrsr { margin: 0; padding: 0; list-style-type: none; } .zg_hrsr_item { margin: 0 0 0 10px; } .zg_hrsr_rank { display: inline-block; width: 80px; text-align: right; } #634 in Books > Computers & Technology > Computer Science > #809 in Kindle Store > Kindle eBooks > Computers & Technology > Computer Science > #1289 in Books > Computers & Technology > Programming >.
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