DataRobot Blog

NOVEMBER 15, 2022

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. Closing the Value Gap: Reducing AI Cycle Time.

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Big Data Experimentation Data-driven Machine Learning 52

CIO Business Intelligence

JULY 6, 2022

Laying the foundation for its cloud strategy, BNY Mellon undertook a multi-year application modernization effort. “In On BNY Mellon’s cloud strategy: First and foremost, we view cloud as a journey, not a destination. Today, our strategy is to have a multi-cloud approach. What follows are edited excerpts of that conversation.

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Experimentation Testing Strategy Risk 85

The Unofficial Google Data Science Blog

APRIL 23, 2024

It is also a sound strategy when experimenting with several parameters at the same time. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. (And sometimes even if it is not[1].) We use these designs frequently, and so can you.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Data Science 101

OCTOBER 15, 2023

And we are still in the science to tech phase, not just battling incredibly challenging lab work, but finding things we can solve. This problem can be witnessed in the business strategies of QC companies. Others like Rigetti and IonQ went public early (the former risking delisting and the latter a huge SPAC). That’s a risk.

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Risk Marketing Consulting Technology 107

CIO Business Intelligence

OCTOBER 1, 2022

It has moved past what Cretella calls the “experimentation phase” with scaled solutions and increasingly sophisticated AI applications. Data and AI have since become central to the company’s digital strategy. “We P&G took the first steps in its AI journey more than five years ago.

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Manufacturing Digital Transformation IoT Internet of Things 144

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. It analyzes historical data and news articles, confirming a possible market correction.

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Cost-Benefit Modeling Manufacturing Interactive 95

FineReport

DECEMBER 11, 2019

In the past few years, the term “data science” has been widely used, and people seem to see it in every field. Big Data”, “Business Intelligence”, “ Data Analysis ” and “ Artificial Intelligence ” came into being. For a while, everyone seems to have begun to learn data analysis. Big data is changing our world.

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Big Data Statistics Experimentation Data Strategy 98

Ontotext

NOVEMBER 2, 2023

This shift from relational to graph approach has been well-documented by Gartner who advise that “using graph techniques at scale will form the foundation of modern data and analytics” and “graph technologies will be used in 80% of data and analytics innovations by 2025.”

IT 69

IT Cost-Benefit Data-driven Technology 69

The Unofficial Google Data Science Blog

JULY 22, 2020

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

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Experimentation Statistics Testing Strategy 95

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

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Management Experimentation B2B Machine Learning 363

Domino Data Lab

JUNE 10, 2020

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. Domino’s best-in-class Workbench is now even more powerful for data scientists.

Data Science 82

Data Science Enterprise Experimentation Modeling 82

IBM Big Data Hub

JANUARY 17, 2023

With IBM’s data integration portfolio, you are not locked into just a single integration style. You can select a hybrid integration strategy that aligns with your organization’s business strategy to meet the needs of your data consumers wanting to access and utilize the data. Data science and MLOps.

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Data-driven Enterprise Data Governance Prescriptive Analytics 57

IBM Big Data Hub

OCTOBER 20, 2023

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

Machine Learning 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

CIO Business Intelligence

OCTOBER 4, 2023

“Generative AI is just more far-reaching than traditional AI or machine learning, so the opportunities for disasters have grown,” says Bret Greenstein, partner and leader of the gen AI go-to-market strategy at PricewaterhouseCoopers. Artificial Intelligence, Data Management, Data Science, Machine Learning

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Cost-Benefit Manufacturing Machine Learning Experimentation 135

The Unofficial Google Data Science Blog

JUNE 30, 2016

By IVAN DIAZ & JOSEPH KELLY Determining the causal effects of an action—which we call treatment—on an outcome of interest is at the heart of many data analysis efforts. In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects.

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Statistics Optimization Modeling Experimentation 44

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

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Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. They have the foundations of data infrastructure. Yet, this challenge is not insurmountable.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

SEPTEMBER 27, 2023

By suggesting a number of use cases, we further encourage experimentation and creative application.” Dayforce Labs is complemented by our data science team, as there is no AI without data,” Lloyd says. This includes carefully examining how data can be used to create better outcomes through AI.”

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Strategy Risk Data-driven Modeling 122

Domino Data Lab

AUGUST 26, 2019

Models are at the heart of of data science and increasing predictive accuracy of models is a core expectation upon industry. The project also covers building a pipeline for automating ML workflow and stay tuned for additional hyperparamater content on the Domino Data Science blog. In [1]: # setup. 0.9333 0.9667 1. ].

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Testing Modeling Machine Learning Metrics 79

CIO Business Intelligence

AUGUST 1, 2023

As many CIOs prepare their 2024 budgets and digital transformation priorities, developing a strategy that seeks opportunities to evolve business models, targets near-term operational impacts, prioritizes where employees should experiment, and defines AI-related risk-mitigating plans is imperative.

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Digital Transformation Unstructured Data Strategy Experimentation 97

CIO Business Intelligence

APRIL 15, 2024

Proceeding with caution While H&R Block’s leadership and board were enticed by the possibilities of gen AI, Lowden notes he had to address some concerns before they fully bought into the project, especially with regard to safety and data privacy. “No No one wants to implement AI that has a high risk of bias,” he says. “We

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Testing Experimentation Data Quality Machine Learning 76

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Although these difficulties are more pronounced when we deal with observational data, the proliferation of hypotheses and lack of intentionality in data collection can even impact designed experiments. Be sure to have a deep, thorough understanding of how data under consideration was collected and what it actually means.

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Experimentation Testing Statistics Metrics 61

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

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OLAP Data Lake Data-driven Snapshot 92