Emerging Paradigms in Machine Learning
Sheela Ramanna · Lakhmi C Jain · Robert J. Howlett
ጁላይ 2012 · Smart innovation, systems, and technologies መጽሐፍ 13 · Springer Science & Business Media
ኢ-መጽሐፍ
498
ገጾች
reportየተሰጡት ደረጃዎች እና ግምገማዎች የተረጋገጡ አይደሉም የበለጠ ለመረዳት
ስለዚህ ኢ-መጽሐፍ
This book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The multidisciplinary nature of machine learning makes it a very fascinating and popular area for research. The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems. Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.
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ምን እንደሚያስቡ ይንገሩን።
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የኮምፒውተርዎን ድር አሳሽ ተጠቅመው በGoogle Play ላይ የተገዙ ኦዲዮ መጽሐፍትን ማዳመጥ ይችላሉ።
ኢሪደሮች እና ሌሎች መሳሪያዎች
እንደ Kobo ኢ-አንባቢዎች ባሉ ኢ-ቀለም መሣሪያዎች ላይ ለማንበብ ፋይል አውርደው ወደ መሣሪያዎ ማስተላለፍ ይኖርብዎታል። ፋይሎቹን ወደሚደገፉ ኢ-አንባቢዎች ለማስተላለፍ ዝርዝር የእገዛ ማዕከል መመሪያዎቹን ይከተሉ።
