BigDataFr recommends: Big Data Analytics = Machine Learning + Cloud Computing […]In this chapter we review historical aspects of the term « Big Data » and the associated analytics. We augment 3Vs with additional attributes of Big Data to make it more comprehensive and relevant. We show that Big Data is not just 3Vs, but 32 Vs, […]
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[Datasciencecentral] BigDataFr recommends: All About Data Science And Big Data #datascientist
BigDataFr recommends: All About Data Science And Big Data Data Science is the system used to extract insights from data that’s mined from various sources. Using various techniques including predictive modeling, Data Science helps to analyze and interpret vast amounts of data. The people who apply Data Science to manage large amounts of data are […]
[arXiv] BigDataFr recommends: Strategies and Principles of Distributed Machine Learning on Big Data #datascientist
BigDataFr recommends: Strategies and Principles of Distributed Machine Learning on Big Data ? The rise of Big Data has led to new demands for Machine Learning (ML) systems to learn complex models with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics thereupon. In order to […]
[arXiv] BigDataFr recommends: Measuring Social Well Being in The Big Data Era: Asking or Listening?
BigDataFr recommends: Measuring Social Well Being in The Big Data Era: Asking or Listening? The literature on well being measurement seems to suggest that « asking » for a self-evaluation is the only way to estimate a complete and reliable measure of well being. At the same time « not asking » is the only way to avoid biased […]
[Datasciencecentral] BigDataFr recommends: Data Mining for Predictive Social Network Analysis
BigDataFr recommends: Data Mining for Predictive Social Network Analysis Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become […]
[arXiv] BigDataFr recommends: Privacy by design in big data: An overview of privacy enhancing technologies #datascientist
BigDataFr recommends: Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics The extensive collection and processing of personal information in big data analytics has given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling, and disclosure of private data. To reap the […]
[arXiv] BigDataFr recommends: Scalable and Accurate Online Feature Selection for Big Data
BigDataFr recommends: Scalable and Accurate Online Feature Selection for Big Data Feature selection is important in many big data applications. There are at least two critical challenges. Firstly, in many applications, the dimensionality is extremely high, in millions, and keeps growing. Secondly, feature selection has to be highly scalable, preferably in an online manner such […]
[Datasciencecentral] BigDataFr recommends: Interview with Gideon Mann, Head of Data Science at Bloomberg #datascientist
BigDataFr recommends: Interview with Gideon Mann, Head of Data Science at Bloomberg Interview with Gideon Mann, Head of Data Science at Bloomberg, where he guides the strategic direction for machine learning, natural language processing, and search on the core terminal. He joined Bloomberg from Google Research. At Google, in addition to academic research, his team […]
[arXiv] BigDataFr recommends: Big Data and Business Intelligence: Debunking the Myths
BigDataFr recommends: Big Data and Business Intelligence: Debunking the Myths Big data is one of the most discussed, and possibly least understood, terms in use in business today. Big data is said to offer not only unprecedented levels of business intelligence concerning the habits of consumers and rivals, but also to herald a revolution in […]
[arXiv] BigDataFr recommends: Making problems tractable on big data via preprocessing with polylog-size output
BigDataFr recommends: Making problems tractable on big data via preprocessing with polylog-size output To provide a dichotomy between those queries that can be made feasible on big data after appropriate preprocessing and those for which preprocessing does not help, Fan et al. developed the ⊓-tractability theory. This theory provides a formal foundation for understanding the […]