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Social media has transformed society and the way people interact with each other. The volume and speed in which new content is being generated surpasses the processing capacity of machine learning systems. Analyzing such data demands new approaches coming from natural language processing, text mining, sentiment analysis, etc to understand and resolve the arising challenges. There is a need to develop robust and adaptable systems to tackle these open issues in real time, as well as to provide a meaningful summarization and visualization to the end users. This book provides the reader with a comprehensive overview of the latest developments in social media and machine learning, addressing research innovations, applications, trends, and open challenges in this crucial area.
Machine learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Machine learning
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This workshop is to bring together researchers, practitioners, and scientific communities to discuss methods that utilize extreme scale systems for machine learning This workshop will focus on the greatest challenges in utilizing HPC for machine learning and methods for exploiting data parallelism, model parallelism, ensembles, and parameter search We invite researchers and practitioners to participate in this workshop to discuss the challenges in using HPC for machine learning and to share the wide range of applications that would benefit from HPC powered machine learning.
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The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neutral networks.
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