Dataiku

MAY 12, 2022

Estimating risk is the essential ingredient to determine the price of an insurance policy. The estimated risk of an insurance policy is the minimum price an insurer should quote to be breakeven, therefore evaluating this risk with precision and confidence is the foundation of a robust quoting system.

Insurance 59

Insurance Breakeven Modeling Statistics 59

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 277

Modeling Machine Learning Risk Advertising 277

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

IBM Big Data Hub

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. The math demonstrates a powerful truth All predictive models, including AI, are more accurate when they incorporate diverse human intelligence and experience.

Predictive Modeling 87

Predictive Modeling Modeling Risk Statistics 87

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Models can be designed, for instance, to discover relationships between various behavior factors.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

CIO Business Intelligence

MAY 9, 2024

Companies want candidates who can drive innovation, deliver meaningful business results, and work closely with other leaders to manage risks. And they must develop and upskill talent to ensure the workforce is well-versed in the innovation and risk associated with AI use. The same can be said for AI talent in general, Daly stresses.

Risk Management 138

Risk Management Risk Cost-Benefit Technology 138

DataRobot Blog

DECEMBER 6, 2022

Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. Bureau of Labor Statistics predicts that the employment of data scientists will grow 36 percent by 2031, 1 much faster than the average for all occupations. Read the blog. Read the blog.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 83

Metrics Machine Learning Risk Statistics 83

DataKitchen

MARCH 12, 2024

Our vision was to create a flexible, state-of-the-art data infrastructure that would allow our analysts to transform the data rapidly with a very low risk of error. Data errors can cause compliance risks. .” — Associate Director, Insights, Top 10 global pharmaceutical company. That was amazing for the team.”

Metrics 117

Metrics Software Cost-Benefit Testing 117

IBM Big Data Hub

MARCH 7, 2023

The worldwide statistics on premature births are staggering— the University of Oxford estimates that neonatal sepsis causes 2.5 The challenge was gleaning relevant insights from the vast amount of data collected to help identify those infants at risk. million infant deaths annually.

Risk 52

Risk Technology Informatics Predictive Modeling 52

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman. ” Watsonx.ai ” Watsonx.ai

Management 82

Management IT Machine Learning Metrics 82

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 122

Enterprise Modeling Testing Data-driven 122

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%).

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

CIO Business Intelligence

OCTOBER 4, 2023

There’s also strong demand for non-certified security skills, with DevSecOps, security architecture and models, security testing, and threat detection/modelling/management attracting the highest pay premiums. The premium it attracts rose by more than 10%, making it the fastest-rising AI-related certification.

Prescriptive Analytics 134

Prescriptive Analytics IT Machine Learning Risk 134

Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Data science needs knowledge from a variety of fields including statistics, mathematics, programming, and transforming data. Mathematics, statistics, and programming are pillars of data science. Statistics.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

Smart Data Collective

OCTOBER 8, 2023

The Power of Data Analytics: An Overview Data analytics, in its simplest form, is the process of inspecting, cleansing, transforming, and modeling data to unearth useful information, draw conclusions, and support decision-making. It is an interdisciplinary field, combining computer science, statistics , mathematics, and business intelligence.

Data Analytics 93

Data Analytics Analytics Statistics Data Collection 93

Smart Data Collective

JULY 16, 2023

The Imperative of Risk Mitigation A crucial element in the world of financial investments is effective hedge fund management. Optimizing hedge fund performance requires the implementation of intelligent strategies, from managing risks to maximizing returns, improving investor relations, and adapting to shifting market conditions.

ROI 71

ROI Data Analytics Analytics Risk Management 71

DataRobot Blog

SEPTEMBER 1, 2022

For example, a recent IDC study 1 shows that it takes about 290 days on average to deploy a model into production from start to finish. Once you move your model into production, you need to monitor and manage your models to ensure that you can trust predictions and turn them into the right business decisions.

Metrics 145

Metrics Statistics Modeling Data Science 145

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 91

Testing Finance Enterprise Modeling 91

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

JUNE 16, 2022

A major reason for this overwhelming lack of success is the failure to establish an operational model aligned with a world in which strategic pivots need to happen quickly. Value Stream Management (VSM) has become increasingly prevalent as the best operational model for those few organizations that have successfully transformed.

Digital Transformation 137

Digital Transformation Statistics Sales Measurement 137

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. Predictive Analytics can help businesses in reducing risk (eg. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

AUGUST 24, 2023

Gen AI has the potential to magnify existing risks around data privacy laws that govern how sensitive data is collected, used, shared, and stored. We’re getting bombarded with questions and inquiries from clients and potential clients about the risks of AI.” The risk is too high.” Not without warning signs, however.

Uncertainty 98

Uncertainty Risk Testing Enterprise 98

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. Predictive Analytics can help businesses in reducing risk (eg. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

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 56

Machine Learning Data Science Statistics Deep Learning 56

IBM Big Data Hub

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Data Governance 54

Data Governance Enterprise Modeling Risk 54

Rocket-Powered Data Science

JULY 19, 2023

This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Ontotext

SEPTEMBER 1, 2023

Terms related to GenAI such as hallucinations and Large Language Models (LLMs) have become lingua-franca for any and every business conversation. Generative AI refers to computational models that are trained on massive amounts of text data and output in the form of text, images, video, audio, new data, and even code.

Risk 52

Risk Modeling Data Quality Data Governance 52

O'Reilly on Data

JULY 28, 2020

You must detect when the model has become stale, and retrain it as necessary. This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. Fault Tolerant Versus Fault Intolerant AI Problems.

Marketing 362

Marketing Experimentation Metrics Testing 362

DataKitchen

NOVEMBER 18, 2022

DataOps Observability must also store run data over time for root cause diagnosis and statistical process control analysis. the data, the models, the integrations, the reports, and the outputs that your customers see?are Real-time details are not the only purpose for setting and measuring against expectations. Testing at Every Step.

Testing 130

Testing Statistics Measurement Metrics 130

DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

CIO Business Intelligence

JANUARY 9, 2024

To get past those points, Colisto worked to educate leaders about the capabilities and risks of AI, seeking to move the company from “no to know.” Similarly, the 2023 US AI Risk Survey Report from professional services firm KPMG found that data integrity was No. What is our appetite for risk and how do we address it?

IT 136

IT Risk Cost-Benefit Enterprise 136

O'Reilly on Data

MARCH 31, 2020

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. For any given input, the same program won’t necessarily produce the same output; the output depends entirely on how the model was trained.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143