CIO Business Intelligence

OCTOBER 3, 2024

It’s a natural fit and will be interesting to see how these ensemble AI models work and what use cases will go from experimentation to production,” says Dyer. LLMs can drive significant insights in compliance, regulatory reporting, risk management, and customer service automation in financial services.

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). Functionality comparison cheat sheet.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 105

IT Digital Transformation IoT Cost-Benefit 105

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

Deep Learning 64

Deep Learning Experimentation Machine Learning Data mining 64

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 90

Unstructured Data Cost-Benefit Machine Learning Experimentation 90

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

Domino Data Lab

JULY 2, 2019

Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Here’s a sampler of related papers and articles if you’d like to dig in further: “ Synthesizing Programs with Deep Learning ” – Nishant Sinha (2017-03-25). “ Software writes Software?

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

CDW Research Hub

AUGUST 21, 2019

AI applications include consumer sentiment analysis, market prediction and fraud risk, drug discovery and genomics, video classification, medical imaging, language processing, and sensor analysis, and numerous other AI use cases. The kit helps facilitate clients’ AI adoption journey from experimentation to production.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

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. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

JUNE 12, 2023

Of course, he says, it’s interesting to try something experimental, but investing requires greater commitment to the business case. This also creates the risk of building a digital legacy with solutions that work on their own, but can’t be connected well together,” he says. It’s the simplest trick,” he says.

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. AGI wouldn’t just perceive its surroundings; it would understand them.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 364

Marketing Experimentation Metrics Testing 364

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. First, 82% of the respondents are using supervised learning, and 67% are using deep learning. 58% claimed to be using unsupervised learning. Bottlenecks to AI adoption.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Domino Data Lab

MAY 8, 2019

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. For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CIO Business Intelligence

MAY 14, 2024

Like many public health agencies across the US, the King County Medical Examiner’s Office tracks drug overdose deaths to target interventions for populations at risk and save lives. The ML models include classic ML and deep learning to predict category labels from the narrative text in reports.

Machine Learning 97

Machine Learning Deep Learning Reporting Experimentation 97

O'Reilly on Data

SEPTEMBER 11, 2019

Deep learning,” for example, fell year over year to No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. 106, +12) also improved, year over year—are rampant, ML-related tools and techniques are not. 40; it peaked at Strata NY 2018 at No. Neural network” also fell slightly from 2018 (No.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

O'Reilly on Data

JANUARY 7, 2020

In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products—and a majority of companies are starting to adopt machine learning. To stay competitive, data scientists need to at least dabble in machine and deep learning.

Deep Learning 293

Deep Learning Machine Learning Experimentation Modeling 293

CIO Business Intelligence

MAY 6, 2025

Predictive analytics: Turning insight into foresight Predictive analytics uses historical data and statistical models or machine learning algorithms to answer the question, What is likely to happen? These capabilities are no longer theoretical or experimental. This is where analytics begins to proactively impact decision-making.

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78