O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. While useful, these constructs are not beyond criticism.

Management 317

Management Machine Learning Metrics Modeling 317

CIO Business Intelligence

FEBRUARY 20, 2025

In addition, they can use statistical methods, algorithms and machine learning to more easily establish correlations and patterns, and thus make predictions about future developments and scenarios. Companies should then monitor the measures and adjust them as necessary.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Smart Data Collective

APRIL 18, 2019

Everyone wants to leverage machine learning, behavior analytics, and AI so IT teams can “up the ante” against attackers. The reality is that “AI solutions” today are based more in machine learning and behavior analytics , which does NOT equate to higher levels of human intelligence and complex decision making.

Behavioral Analytics 98

Behavioral Analytics Advertising Uncertainty Machine Learning 98

DataRobot

AUGUST 5, 2021

AI and Uncertainty. Some people react to the uncertainty with fear and suspicion. Recently published research addressed the question of “ When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making.”. People are unsure about AI because it’s new. AI you can trust.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

CIO Business Intelligence

JANUARY 11, 2024

To get back in front, IT leaders will have to transform lessons learned from 2023 into actionable, adaptable processes, as veteran technology pros have been remarkably consistent in identifying global and economic uncertainties as key challenges for IT leaders to anticipate in 2024 as well.

IT 133

IT Uncertainty Cost-Benefit Strategy 133

Cloudera

DECEMBER 3, 2021

This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. Systems should be designed with bias, causality and uncertainty in mind. Uncertainty is a measure of our confidence in the predictions made by a system. System Design. Model Drift.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

Jen Stirrup

NOVEMBER 15, 2022

The foundation should be well structured and have essential data quality measures, monitoring and good data engineering practices. Of course, the findings need to add value, but how do we measure this success? Measures can be financial, tying in with the business strategy. After all, it can sound a bit woolly!

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against. Dimensions of Trust.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. After navigating the complexity of multiple systems and stages to bring data to its end-use case, the final product’s value becomes the ultimate yardstick for measuring success.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. The resulting structured data is then used to train a machine learning algorithm. There are a lot of image annotation techniques that can make the process more efficient with deep learning.

Machine Learning 93

Machine Learning Metrics Uncertainty Deep Learning 93

CIO Business Intelligence

JUNE 8, 2022

Digital disruption, global pandemic, geopolitical crises, economic uncertainty — volatility has thrown into question time-honored beliefs about how best to lead IT. Thriving amid uncertainty means staying flexible, he argues. . When it comes to data and analytics, test, learn and recalibrate. Some hires may need to be postponed.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

MARCH 18, 2024

The researchers discovered that workers who used three of these technologies — AI and machine learning software, wearable trackers for surveillance, and robotics — reported a lower level of health-related well-being, according to a widely used standardized measurement. using wearables, 20.8% AI software, and 23.7%

Technology 97

Technology Machine Learning Uncertainty Interactive 97

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. In “Are Your Machine Learning Models Wrong” , Richard Harmon explores what financial institutions should do in the face of the uncertainty caused by COVID-19. Data Variety. What if 2020 is an anomaly?

Insurance 95

Insurance Digital Transformation Unstructured Data Machine Learning 95

O'Reilly on Data

JULY 20, 2021

This measurement of trust and risk is benefited by understanding who could be in front of the device. We can’t forget that the machine learning that is doing biometrics is not a deterministic calculation; there is always some degree of uncertainty.

Risk 337

Risk Software Interactive Modeling 337

Domino Data Lab

JUNE 2, 2019

Secondly, I talked backstage with Michelle, who got into the field by working on machine learning projects, though recently she led data infrastructure supporting data science teams. Just doing machine learning is not enough, and sometimes not even necessary.”. First off, her slides are fantastic! Nick Elprin.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

DataRobot

APRIL 5, 2021

The uncertainty in her reply piqued my interest. In a series of experiments, the researchers and authors of “ Manipulating and Measuring Model Interpretability ” asked participants to predict apartment prices with the assistance of a machine learning model. Umm, yes, I think so,” she replied.

Machine Learning 96

Machine Learning Uncertainty Modeling Reporting 96

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. The consumer lending business is centered on the notion of managing the risk of borrower default. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry.

Predictive Analytics 83

Predictive Analytics Analytics Data mining Cost-Benefit 83

CIO Business Intelligence

SEPTEMBER 9, 2024

Additionally, private equity-owned businesses now recognize that effective technology leadership extends beyond cost-cutting measures,” she says. When a CIO is replaced it’s with someone who has AI or machine learning experience who knows how to make those initiatives successful, he says. That’s what’s driving salaries up.

Marketing 124

Marketing Machine Learning Uncertainty Technology 124

CIO Business Intelligence

SEPTEMBER 12, 2022

One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

CIO Business Intelligence

JUNE 30, 2022

Even with countless ambiguities present in legal and compliance arenas and ongoing uncertainty in the global, national and regional data privacy landscape, the relevance of a sovereign cloud as part of the journey toward digital sovereignty is more significant now than ever before.

Uncertainty 98

Uncertainty Metadata Machine Learning Data Governance 98

CIO Business Intelligence

JULY 5, 2022

Even with countless ambiguities present in legal and compliance arenas and ongoing uncertainty in the global, national and regional data privacy landscape, the relevance of a sovereign cloud as part of the journey toward digital sovereignty is more significant now than ever before.

Uncertainty 98

Uncertainty Metadata Machine Learning Data Governance 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. Forecasting at the “push of a button”?

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

CIO Business Intelligence

FEBRUARY 23, 2023

The former rely on batch processing to train machine learning models and generate features (measurable properties of a phenomenon). He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. Artificial Intelligence, IT Leadership

Uncertainty 98

Uncertainty Strategy Data-driven Machine Learning 98

AWS Big Data

AUGUST 7, 2023

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. UCI Machine Learning Repository.

Forecasting 98

Forecasting Data Warehouse Machine Learning Modeling 98

AWS Big Data

SEPTEMBER 5, 2024

Intuitively, for some extremely short user inputs, the vectors generated by dense vector models might have significant semantic uncertainty, where overlaying with a sparse vector model could be beneficial. Based on our experience of RAG, we measured recall@1, recall@4, and recall@10 for your reference.

Metrics 110

Metrics Testing Experimentation Modeling 110

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This type of data is often collected through less rigid, measurable means than quantitative data. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

DataRobot

JUNE 1, 2021

AI and machine learning are fields rife with potential security issues. Recognizing and admitting uncertainty is a major step in establishing trust. Interventions to manage uncertainty in predictions vary widely. Protecting Sensitive Data. Knowing When to Trust a Model. Is rain 40% likely? Deploying Good Governance.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

BI-Survey

FEBRUARY 14, 2022

Overnight, the impact of uncertainty, dynamics and complexity on markets could no longer be ignored. Local events in an increasingly interconnected economy and uncertainties such as the climate crisis will continue to create high volatility and even chaos. The COVID-19 pandemic caught most companies unprepared. BARC Recommendations.

Forecasting 52

Forecasting Uncertainty Measurement Cost-Benefit 52

Sisense

SEPTEMBER 9, 2019

Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Following a few false starts and some great iterative learning with the BigSquid team, we came away with a solid predictive data model of the warranty costs for future periods.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Data-driven Forecasting 75

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., Crucially, it takes into account the uncertainty inherent in our experiments. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

JANUARY 4, 2023

Moving forward, we will see workflows that are more capable and widely adopted to facilitate edge-core-cloud needs like generating meshes, performing 3D simulations, performing post-simulation data analysis, and feeding data into machine learning models—which support, guide, and in some case replace the need for simulation.

Cost-Benefit 59

Cost-Benefit Machine Learning Uncertainty Modeling 59

The Unofficial Google Data Science Blog

AUGUST 27, 2019

A machine learning classifier serves this task perfectly. The measurement may be biased if our samples are generated from a procedure that samples without replacement, such as reservoir sampling , especially if some items have disproportionate weight, i.e., $p(v_i) cdot n$ is large. High Risk 10% 5% 33.3% How Many Strata?

Metrics 98

Metrics Statistics Uncertainty Optimization 98

The Unofficial Google Data Science Blog

APRIL 19, 2021

Practical Reason #2: Model Modularity In complex machine learning systems, models depend on each other. The numerical value of the signal became decoupled from the event it was measuring even as the ordinal value remained unchanged. bar{pi} (1 - bar{pi})$: This is the irreducible loss due to uncertainty.

Modeling 122

Modeling IT Metrics Testing 122

Cloudera

NOVEMBER 19, 2018

One of Cloudera’s partners offers “Sustainability Services” with a goal of assisting organizations in turning costs and risks associated with changing regulatory and workforce environments, as well as supply chain uncertainties and volatile markets, into business opportunities.

Digital Transformation 40

Digital Transformation IoT Cost-Benefit Uncertainty 40

bridgei2i

OCTOBER 20, 2021

Slowly and gradually, the industry trend shifted to the online sensors where you don’t have to run around just for the measurement. Considering the current situation, I will not say that, you know, it is a COVID situation, because we don’t know, when COVID will be over.

Manufacturing 98

Manufacturing Enterprise IoT Technology 98