O'Reilly on Data

NOVEMBER 13, 2018

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. Classification parity means that one or more of the standard performance measures (e.g., As we deploy more models, it’s becoming clear that we will need to think beyond optimizing statistical and business metrics.

Machine Learning 220

Machine Learning Risk Management Statistics 220

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

IBM Big Data Hub

MARCH 26, 2024

While ESG seeks to provide standard methods and approaches to measuring across environmental, social and governance KPIs, and holds organizations accountable for that performance, sustainability is far broader. How is sustainability managed—as an annual measuring exercise or an ongoing effort that supports business transformation?

Measurement 68

Measurement Metrics Strategy Reporting 68

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 56

Risk Machine Learning Risk Management Measurement 56

O'Reilly on Data

OCTOBER 18, 2022

As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. applies external authoritative standards from laws, regulations, and AI risk management frameworks. Bias is about more than data and models.

Risk Management 291

Risk Management Risk Testing Measurement 291

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66