Cloudera

APRIL 9, 2021

Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. Predictive Analytics – AI & machine learning. This integration is key in assuring that models evolve with the data – to avoid, for example, model drift.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 332

Management Machine Learning Experimentation Metrics 332

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130

CIO Business Intelligence

NOVEMBER 7, 2022

CIOs seeking big wins in high business-impacting areas where there’s significant room to improve performance should review their data science, machine learning (ML), and AI projects. CIOs and CDOs should lead ModelOps and oversee the lifecycle Leaders can review and address issues if the data science teams struggle to develop models.

Machine Learning 128

Machine Learning Data Science Experimentation IoT 128

O'Reilly on Data

JANUARY 11, 2022

This trend started with the gigantic language model GPT-3. This may encourage the creation of more large-scale models; it might also drive a wedge between academic and industrial researchers. What does “reproducibility” mean if the model is so large that it’s impossible to reproduce experimental results?

Experimentation 297

Experimentation Modeling Strategy Machine Learning 297

Cloudera

JULY 27, 2021

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. We believe the best way to learn what a technology is capable of is to build things with it.

Data Science 111

Data Science Enterprise Experimentation Machine Learning 111

DataRobot

JUNE 17, 2021

At the time, I had a small following of people interested in using Eureqa to derive mathematical formulas and models. Traditionally, science has advanced in many cases by having brilliant researchers compete different hypotheses to explain experimental data, and then design experiments to measure which is correct. So What is Eureqa?

Modeling 52

Modeling Experimentation Machine Learning Measurement 52

CIO Business Intelligence

APRIL 29, 2024

They need to have a culture of experimentation.” The same Gartner forecast, using survey results from late 2023, found that 55% percent of all companies planned to deploy AI or machine learning tools by the end of this year. CIOs should be “change agents” who “embrace the art of the possible,” he says.

Experimentation 135

Experimentation Forecasting Risk Consulting 135

Domino Data Lab

NOVEMBER 14, 2019

James Murdoch, Chandan Singh, Karl Kumber, and Reza Abbasi-Asi’s recent paper, “Definitions, methods, and applications in interpretable machine learning” Introduction. Model interpretability continues to spark public discourse among industry. Yet there are tradeoffs to consider when selecting a model.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

FEBRUARY 16, 2024

ADP combines various datasets and analytics technologies and builds algorithms and machine learning models to develop custom solutions for its clients, such as determining salary ranges for nurses in a specific state that a healthcare client may be evaluating for relocation.

Digital Transformation 116

Digital Transformation Experimentation Cost-Benefit Machine Learning 116

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: Columbia University Price: Students pay Columbia Engineering’s rate of tuition (US$2,362 per credit).

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Dataiku

MAY 23, 2023

Once a data science project has progressed through the stages of data cleaning and preparation, analysis and experimentation, modeling, testing, and evaluation, it reaches a critical point.

Data Science 52

Data Science Experimentation Machine Learning Testing 52

Cloudera

JANUARY 30, 2019

Data scientists require on-demand access to data, powerful processing infrastructure, and multiple tools and libraries for development and experimentation. To move beyond laptop experimentation to impacting the business, data teams also need seamless sharing and native integration with the production data platform. Sound familiar?

Data Science 71

Data Science Machine Learning Experimentation Cost-Benefit 71

Decision Management Solutions

DECEMBER 17, 2021

In the recent McKinsey article discussing designing next-generation credit-decisioning models they outlined four best practices for automated credit-decisioning models for banks as they continue their digital transformations. Digital lending based on high-performance credit-decisioning models, says McKinsey, lead to: Increased revenue.

Modeling 52

Modeling Experimentation Visualization Risk 52

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. What’s driving this growth? disproportionately involve Python. What’s in a name?

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

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.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Drag-and-drop Modeler for creating pipelines, IBM integrations.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

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. Luckily, many are expanding budgets to do so. “94%

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

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.

Deep Learning 72

Deep Learning Experimentation Machine Learning Risk 72

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. Five years later, transformer architecture has evolved to create powerful models such as ChatGPT. Meanwhile, however, many other labs have been developing their own generative AI models.

Experimentation 116

Experimentation Enterprise Deep Learning Modeling 116

DataRobot Blog

NOVEMBER 15, 2022

A packed keynote session showed how repeatable workflows and flexible technology get more models into production. Our in-booth theater attracted a crowd in Singapore with practical workshops, including Using AI & Time Series Models to Improve Demand Forecasting and a technical demonstration of the DataRobot AI Cloud platform.

Big Data 52

Big Data Experimentation Data-driven Machine Learning 52

CIO Business Intelligence

DECEMBER 6, 2023

Enabling consistency in the data sets from these varied sites is integral to DS Smith’s analytics strategy, as well as for anticipated changes in the company’s technology and business models, Dickson says. 2, machine learning/AI (31%), the packaging company has three use cases in proof of concept. As for No.

Manufacturing 97

Manufacturing Data Lake Digital Transformation Machine Learning 97

IBM Big Data Hub

MAY 25, 2023

The Center of Excellence (CoE) already has more than 1,000 consultants with specialized generative AI expertise that are engaging with a global set of clients to drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models.

Consulting 108

Consulting Experimentation Machine Learning Modeling 108

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

Experimentation 82

Experimentation Modeling Deep Learning Data-driven 82

CIO Business Intelligence

JANUARY 9, 2024

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4) See [link].

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.

Unstructured Data 94

Unstructured Data Cost-Benefit Experimentation Machine Learning 94

CIO Business Intelligence

APRIL 12, 2024

As part of the rollout, each store is upgraded with an edge computing solution that leverages a container solution for point-of-sale devices, the management of security cameras, AI voice communications, and AI models with computer vision.

Experimentation 114

Experimentation Sales Digital Transformation Metrics 114

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

Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision.

Data Warehouse 83

Data Warehouse Experimentation Cost-Benefit Dashboards 83

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We

Recreation/Entertainment 135

Recreation/Entertainment Experimentation Modeling Data-driven 135

IBM Big Data Hub

DECEMBER 4, 2023

Advacements in machine learning algorithms, neural networks and the computational power of generative AI, combined with human expertise, intuition and creativity, can unlock new possibilities and achieve levels of innovation that were previously unimaginable.

Experimentation 65

Experimentation Modeling Metrics Machine Learning 65