CIO Business Intelligence

MAY 16, 2022

ITIL’s systematic approach to IT service management (ITSM) can help businesses manage risk, strengthen customer relations, establish cost-effective practices, and build a stable IT environment that allows for growth, scale, and change. How does ITIL help business? How does ITIL reduce costs?

IT 103

IT Cost-Benefit ROI Risk 103

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. ” “Data science” was first used as an independent discipline in 2001.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

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

The Unofficial Google Data Science Blog

JUNE 30, 2016

Choose the weights $alpha$ that minimize the cross-validated risk: $hatalpha =argmin_{alpha} frac{1}{J}sum_{j=1}^Jfrac{1}{|mathcal V_j|}sum_{iin mathcal V_j} L(M_i, hat e_{alpha, mathcal T_j})$ subject to $quad 0 leq alpha_kleq 1, sum_{k=1}^Kalpha_k=1,$ and define the final estimator as $hat e_{hatalpha}(x)$. 2001): 5-32.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Domino Data Lab

JULY 22, 2019

What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things. You see these drivers involving risk and cost, but also opportunity. I can point to the year 2001. All righty. Where did this happen?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

AUGUST 27, 2019

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. If we could separate bad videos from good videos perfectly, we could simply calculate the metrics directly without sampling. The missing verdicts create two problems.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic. Chawla et al.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136