AWS Big Data

NOVEMBER 17, 2023

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena.

Optimization 108

Optimization Statistics Metadata Data Lake 108

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

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.

Statistics 44

Statistics Optimization Modeling Experimentation 44

O'Reilly on Data

MAY 27, 2020

In 2001, just as the Lexile system was rolling out state-wide, a professor of education named Stephen Krashen took to the pages of the California School Library Journal to raise an alarm. The report has pages of careful caveats, but in the end it treats these risk-adjusted ratios as a good measure of a surgeon’s performance.

Risk 355

Risk Testing Measurement Reporting 355

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. You see these drivers involving risk and cost, but also opportunity. I can point to the year 2001. Tukey did this paper. All righty.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? In terms of teaching and learning data science, Project Jupyter is probably the biggest news over the past decade – even though Jupyter’s origins go back to 2001! In business terms, why does this matter ?

Data Science 56

Data Science Machine Learning Reporting Visualization 56

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. High Risk 10% 5% 33.3% 2] Lawrence Brown, Tony Cai, Anirban DasGupta (2001). Statistical Science. 16 (2): 101–133. [3]

Metrics 98

Metrics Statistics Uncertainty Optimization 98