BigDataFr recommends: How to Raise a Data -Scientist in the Xbox Age An article by this title (without the ‘Data’) appeared in December in the WSJ written by Robert Scherrer, Chairman of the Physics and Astronomy department at Vanderbilt University. As an educator and parent he has some interesting and humorous insights into how to […]
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[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: Predicting the Future #datascientist
BigDataFr recommends: Predicting the Future TOne of the really fun aspects of being a data scientist is that we are called upon to predict the future. Frequently that means trying to predict who will buy, who will churn, what they will buy next, how much they will spend, all the sorts of questions that are […]
[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: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means Excerpt We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix and therefore subsequent processing, such as PCA or […]
[datasciencecentral] BigDataFr recommends: 5 Warning Signs that Turn Off Data Science Hiring Managers
BigDataFr recommends: 5 Warning Signs that Turn Off Data Science Hiring Managers Excerpt As a hiring manager for data analytics positions, I often complain that there are not enough qualified resumes. Most of the resumes that do get passed on to me from recruiters quickly get filed away. Those job candidates belong to one of […]
[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 […]
[arXiv] BigDataFr recommends: Big Data Analytics-Enhanced Cloud Computing: Challenges, Architectural Elements, and Future Directions
BigDataFr recommends: Big Data Analytics-Enhanced Cloud Computing: Challenges, Architectural Elements, and Future Directions Excerpt The emergence of cloud computing has made dynamic provisioning of elastic capacity to applications on-demand. Cloud data centers contain thousands of physical servers hosting orders of magnitude more virtual machines that can be allocated on demand to users in a pay-as-you-go […]