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Data Science, Past & Future

Domino Data Lab

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

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Edmunds sets stage for AI with data infrastructure consolidation

CIO Business Intelligence

Rokita has been with Edmunds for more than 18 years, starting as executive director of technology in 2005. His role now encompasses responsibility for data engineering, analytics development, and the vehicle inventory and statistics & pricing teams. We believe the same thing is happening right now with AI.

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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

statistical model-based techniques – Using Machine Learning we can streamline and simplify the process of building NER models, because this approach does not need a predefined exhaustive set of naming rules. The process of statistical learning can automatically extract said rules from a training dataset. The CRF model.

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Fitting Bayesian structural time series with the bsts R package

The Unofficial Google Data Science Blog

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering.

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Using random effects models in prediction problems

The Unofficial Google Data Science Blog

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. ICML, (2005). [3] Journal of the American Statistical Association 68.341 (1973): 117-130. [5] Journal of the American Statistical Association, Vol.

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Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

Or when Tableau and Qlik’s serious entry into the market circa 2004-2005 set in motion a seismic market shift from IT to the business user creating the wave of what was to become the modern BI disruption. Research VP, Business Analytics and Data Science. Enjoy your summer!! Thanks for reading and stay tuned. Twitter: @rsallam.