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 58

Machine Learning Data Science Statistics Deep Learning 58

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. It should be noted that inverse probability weighting is not generally optimal (i.e., An excellent review of statistical learning methods may be found in Friedman et.

Statistics 44

Statistics Optimization Modeling Experimentation 44

The Unofficial Google Data Science Blog

AUGUST 27, 2019

This problem can be phrased as an optimization problem — given some fixed review capacity how should we sample videos? Of course, any mistakes by the reviewers would propagate to the accuracy of the metrics, and the metrics calculation should take into account human errors.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

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. The problems down in the mature bucket, those are optimizations, they aren’t showstoppers. I can point to the year 2001.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109