Smart Data Collective

AUGUST 21, 2022

The process of ensuring that your product or software is of the best quality for your clients is referred to as quality assurance testing or QA testing. Performing Quality Assurance Testing with a Security Approach. AI Can Improve Manual Testing in Addition to Automated Testing.

Testing 85

Testing Risk Software Technology 85

DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Smart Data Collective

MAY 7, 2023

million —and organizations are constantly at risk of cyber-attacks and malicious actors. In order to protect your business from these threats, it’s essential to understand what digital transformation entails and how you can safeguard your company from cyber risks. What is cyber risk?

Digital Transformation 105

Digital Transformation Risk Strategy Testing 105

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

Machine Learning 49

Machine Learning Marketing Forecasting Modeling 49

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.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145

Risk Consulting Machine Learning Data Science 145

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. How Machine Learning Helps Detect and Prevent AML. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Area such as: .

Risk 97

Risk Optimization Management Insurance 97

Domino Data Lab

MAY 15, 2019

Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One. Over the years, I have listened to data scientists and machine learning (ML) researchers relay various pain points and challenges that impede their work. Product Management for Machine Learning.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

Smart Data Collective

MAY 24, 2019

Machine learning is playing an increasingly important role in web development. However, advances in machine learning have made them much more robust. One of the most important ways that machine learning is changing the Internet user experience is with the development of progressive web applications (PWAs).

Machine Learning 101

Machine Learning Internet of Things Testing Technology 101

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. This may be accomplished through a wide variety of tests, to develop a deeper introspection into how the model behaves. Figure 2: Feature Effect plot making use of partial dependence within DataRobot.

Risk 52

Risk Modeling Metrics Business Objectives 52

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform. End-to-end Data Lifecycle.

Risk 87

Risk Marketing Technology Management 87

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? Keep it agile, with short design, develop, test, release, and feedback cycles: keep it lean, and build on incremental changes. Test early and often. Test and refine the chatbot.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

DECEMBER 13, 2023

Next-Generation Software Development – New software tools enable modern code-deployment pipelines and automate code generation, testing, refactoring, and translation, improving application quality and development processes CIO, Generative AI

Machine Learning 117

Machine Learning Software Testing Risk 117

KDnuggets

MARCH 17, 2022

Check out this article on using CTGANs to create synthetic datasets for reducing privacy risks, training and testing machine learning models, and developing data-centric AI products.

Machine Learning 139

Machine Learning Testing Risk Modeling 139

BizAcuity

APRIL 19, 2019

The answer lies in revolutionary machine learning and business analytics. Adaptive machine and business analytics, applying cutting-edge machine learning and other technologies are proving helpful in spotting anomalies among users in real-time and fighting this issue. ML and Business Analytics to the rescue.

Machine Learning 75

Machine Learning Metrics Data mining Business Analytics 75

CIO Business Intelligence

APRIL 5, 2024

The EU and US want to foster scientific information exchange between AI experts on either side of the Atlantic in areas such as developing benchmarks and assessing potential risks. At this stage in the development of AI, investment in testing and safety is far more effective than regulation,” Carlsson argued.

Risk 129

Risk Testing Consulting Machine Learning 129

Smart Data Collective

JUNE 7, 2019

Machine learning is playing a very important role in improving the functionality of task management applications. However, recent advances in applying transfer learning to NLP allows us to train a custom language model in a matter of minutes on a modest GPU, using relatively small datasets,” writes author Euan Wielewski.

Machine Learning 77

Machine Learning Software Management Data-driven 77

Rocket-Powered Data Science

JUNE 17, 2022

Here is a list of my top moments, learnings, and musings from this year’s Splunk.conf : Observability for Unified Security with AI (Artificial Intelligence) and Machine Learning on the Splunk platform empowers enterprises to operationalize data for use-case-specific functionality across shared datasets. is here, now!

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. pharmacogenomics) and risk assessment of genetic disorders (e.g., genetic counseling, genetic testing). Churn Labels and Drivers.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Cloudera

MARCH 28, 2019

For all the advances in big data, machine learning and computational simulation in the decade since the global financial crisis, incumbent banks, still preoccupied with the twin imperatives of ever-tougher regulatory compliance and boosting shareholder returns, are playing catch-up in their adoption of new technologies.

Risk 72

Risk Management Risk Management Machine Learning 72

CIO Business Intelligence

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

O'Reilly on Data

NOVEMBER 29, 2022

While it’s unlikely that the bill will become law, merely raising the possibility of criminal prosecution and jail time has upped the ante for “ commercial entities that operate high-risk information systems or automated-decision systems, such as those that use artificial intelligence or machine learning.”. is worth reading.

Machine Learning 278

Machine Learning Recreation/Entertainment Risk Testing 278

DataRobot Blog

JUNE 3, 2022

To understand the capabilities and address the risks of AI, all of us – developers, policy-makers, end-users, bystanders – must have a shared understanding of what AI is, how it can be applied to the benefit of humanity, and the risks involved when implementing it without guardrails in place to mitigate bias and harm. Download now.

Risk 52

Risk Predictive Modeling Modeling Technology 52

Cloudera

OCTOBER 18, 2023

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement — to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. Debugging: Identifying and fixing bugs in code is essential for application security.

Cost-Benefit 76

Cost-Benefit Testing Machine Learning Optimization 76

CIO Business Intelligence

AUGUST 1, 2023

Supporting us with our repository for developers with a kind of a testing deployment architecture for continuous updates and employment and deployment. Moving forward When asked about the future of the program, Dr. Troy is hopeful that technologies such as machine learning and AI can be integrated to help automate processes for linguists.

Risk 98

Risk IT Software Digital Transformation 98

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

IBM Big Data Hub

APRIL 9, 2024

” Watsonx.data uses machine learning (ML) applications to simulate data that represents ball positioning projections. ” Training and testing models The Masters digital team used watsonx.ai “We used few-shot learning to help guide the models,” says Baughman.

Management 82

Management IT Machine Learning Metrics 82

CIO Business Intelligence

MARCH 30, 2022

For organizations looking to move beyond stale reports, decision intelligence holds promise, giving them the ability to process large amounts of data with a sophisticated mix of tools such as artificial intelligence and machine learning to transform data dashboards and business analytics into more comprehensive decision support platforms.

Machine Learning 144

Machine Learning Testing Risk Data-driven 144

CIO Business Intelligence

FEBRUARY 28, 2024

Using these models, healthcare providers can test drugs and therapies with unprecedented speed and accuracy, reducing risks for both patients and physicians. Essentially, the technology involves the replication of the human body in software models.

Informatics 115

Informatics Data-driven Digital Transformation Predictive Analytics 115

O'Reilly on Data

MARCH 26, 2024

It’s ironic that, in this article, we didn’t reproduce the images from Marcus’ article because we didn’t want to risk violating copyright—a risk that Midjourney apparently ignores and perhaps a risk that even IEEE and the authors took on!) joined Flickr. She uploaded some pictures of her children, Chloe and Jasper.

Modeling 275

Modeling Machine Learning Risk Advertising 275

CIO Business Intelligence

DECEMBER 14, 2023

AI and machine learning (ML) can do this by automating the design cycle to improve efficiency and output; AI can analyze previous designs, generate novel design ideas, and test prototypes, assisting engineers with rapid, agile design practices. Generative AI can help mitigate these often serious risks.

Manufacturing 142

Manufacturing Cost-Benefit Unstructured Data Optimization 142

Smart Data Collective

APRIL 18, 2019

AI, which can also be spoken about in terms of machine learning, is all about pattern recognition. Finally, AI-EHR partnerships may help solve one of the biggest issues with EHR software today – test submissions and results. The post Can AI Remove The Risk From EHRs? Why AI Matters.

Risk 72

Risk Testing Software Insurance 72

CIO Business Intelligence

JANUARY 18, 2024

Half of CEOs say their organization is at least somewhat unprepared for AI and machine learning (ML) adoption, according to Workday’s C-Suite Global AI Indicator Report. That’s a big difference with machine learning vs. traditional approaches.” Just 6% say they are fully prepared.)

Finance 126

Finance Machine Learning Risk Management Optimization 126

CIO Business Intelligence

JULY 5, 2023

Artificial intelligence and machine learning are the No. Generative AI is raising the interest level even further as organizations begin testing different use cases for deep-learning models. AI is really doing the heavy lift, in terms of identifying risks,” Crowley says.

Machine Learning 95

Machine Learning Deep Learning Consulting Enterprise 95