Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

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Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

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The Unofficial Google Data Science Blog

JULY 11, 2017

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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Domino Data Lab

SEPTEMBER 25, 2019

Conducting exploratory analysis and extracting meaningful insights from data are core components of research and data science work. Time series data is commonly encountered. We see it when working with log data, financial data, transactional data, and when measuring anything in a real engineering system.

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Domino Data Lab

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. 3f" % x) dataDF.describe().

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The Unofficial Google Data Science Blog

AUGUST 27, 2019

But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem. Statistical Science. Statistics in Biopharmaceutical Research, 2010. [4] 5] Ray Chambers, Robert Clark (2012).

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The Unofficial Google Data Science Blog

JUNE 30, 2016

Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation. The field of statistical machine learning provides a solution to this problem, allowing exploration of larger spaces. For a random sample of units, indexed by $i = 1.

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Alation

JULY 7, 2022

The data scientist. In 2012 Davenport and Patil declared the data scientist was “ The Sexiest Job of the 21st Century.” Universities were only just beginning to plan formal academic data science programs, and the skills to be taught in those programs were still being identified. Why is so much time wasted?

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Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

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The Unofficial Google Data Science Blog

APRIL 17, 2017

In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification. Forecasting data and methods". [2] Journal of Official Statistics 6.1 1990): 3. [3]

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DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. Data Requirements. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. What is MMM?

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The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping. Hedayat, N.J.A.

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The Unofficial Google Data Science Blog

MARCH 31, 2016

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. Cambridge University Press, (2012). [4] Journal of the American Statistical Association 68.341 (1973): 117-130. [5] 4] Bradley Efron, and Carl Morris.

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The Unofficial Google Data Science Blog

MAY 31, 2016

Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. This is a quantity that is easily interpretable and summarizes nicely the statistical power of the experiment. In the U.S., Cambridge, 2007.

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Domino Data Lab

JULY 22, 2019

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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Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

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The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. Data was expensive to gather, and therefore decisions to collect data were generally well-considered. Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data.

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Rita Sallam

SEPTEMBER 11, 2020

We try use the Bake-Offs as a platform for data for good. Rather than just using some solely fun data like football/ soccer statistics – go Mo Salah! – this year, we used population health data. Last year we did loneliness and happiness data. ThoughtSpot. In 2016, life expectancy in the United States (78.5)

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