Cloudera

MARCH 30, 2022

Equifax found this out to their own cost in 2017 when they failed to protect the data of almost 150 million users globally. Making positive progress is about driving collective accountability, rebuilding policy, and focusing on proactive measures. appeared first on Cloudera Blog. Why we Need to Talk about Ethics and Governance.

Data-driven 116

Data-driven Marketing Measurement Modeling 116

Cloudera

MAY 27, 2021

This blog post was written by Pedro Pereira as a guest author for Cloudera. . Turning a blind eye to problems or applying half measures isn’t going to work. In 2017, FaceApp, which uses neural network technology to edit selfies, “ apologized for building a racist algorithm ,” perhaps the first of many such regrets.

Machine Learning 115

Machine Learning Big Data Consulting Technology 115

BizAcuity

MARCH 25, 2019

For event industry, there is a need for their operating systems to store historical data and unless they store this data, the event management company will not be able to measure or understand the revenue analytics trends. Without this information, revenue analytics are worthless.

Analytics 74

Analytics Dashboards Sales Marketing 74

Cloudera

MAY 18, 2021

These interactions are captured and the resulting synthetic data sets can be analysed for a number of applications, such as training models to detect emergent fraudulent behavior, or exploring “what-if” scenarios for risk management. Value-at-Risk (VaR) is a widely used metric in risk management. Intraday VaR. Citations. [1]

Risk 94

Risk Marketing Risk Management Data-driven 94

The Unofficial Google Data Science Blog

APRIL 17, 2017

First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. Facebook in a recent blog post unveiled Prophet , which is also a regression-based forecasting tool. At lastly, "forecasting" for us did not mean anomaly detection.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., This blog post discusses such a comprehensive approach that is used at Youtube. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Challenges for Transparency ”. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. What Are the Risks? Copyright violation is another risk. Tokens are significant parts of a word.

IT 262

IT Modeling Testing Risk 262

Domino Data Lab

MAY 20, 2021

This renders measures like classification accuracy meaningless. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Chawla et al.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Some relate to inherent issues with what is being measured.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? The ability to measure results (risk-reducing evidence).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment. The interval [-a, a] is called a 90% confidence interval.

Statistics 27

Statistics Uncertainty Risk Marketing 27

Insight

DECEMBER 30, 2019

Wikipedia In our last blog , we walked through a super fast introduction of “vanilla” flavored neural networks. In Figure 1, you can see the results of the Harris corner detector applied to an image of Jessie Graff competing in the 2017 American Ninja Warrior Finals: Figure 1?—?Harris Original image is on the left.

Visualization 72

Visualization Modeling Machine Learning IT 72

Domino Data Lab

AUGUST 1, 2021

This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. This is to be expected, as there is no reason for a perfect 50:50 separation of the good vs. bad credit risk. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. The fact is that it is and will affect our lives, whether we like it or not.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Alation

AUGUST 26, 2021

Privacy, Risk and Compliance. HBR Review May/June 2017. Highly regulated industries, like insurance, healthcare, and finance, are traditionally risk averse and subject to compliance audits; historically, their data management strategies were defensive, focused on compliance. Cloud Transformation. Cloud Data Migration.

Metadata 64

Metadata Data Governance Dashboards Software 64