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Advanced Analytics with Spark: Patterns for Learning from Data at Scale
In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.
You’ll start with an... | | The Geography of Networks and R&D Collaborations (Advances in Spatial Science)
The geography of networks and R&D collaborations, in particular the spatial dimension of interactions between organisations performing joint R&D, have attracted a burst of attention in the last decade, both in the scientific study of the networks and in the policy sector. The volume is intended to bring together a selection of... | | Supervised Sequence Labelling with Recurrent Neural Networks
Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range... |
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Infectious Disease InformaticsInfectious Diseases Informatics
Edited by
Vitali Sintchenko
The University of Sydney, Sydney, Australia
Preface.- List of contributors.- 1Informatics for Infectious Disease Research and Control.- 2 Bioinformatics of Microbial Sequences.- 3 Mining Databases for Microbial Gene Sequences.- 4 Comparative Genomics of... | | | | Principles of Model CheckingOur growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a... |
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