DataRobot

FEBRUARY 10, 2021

Machine learning is a glass cannon. Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. As a data scientist, one of my passions is to reproduce research papers as a learning exercise.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). Artificial intelligence (AI) adoption is still in its early stages.

Risk 77

Risk Modeling Management Metadata 77

Decision Management Solutions

MARCH 25, 2019

Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science implementation. 1 – Getting business buy-in.

Insurance 75

Insurance Data Science Testing Modeling 75

DataRobot

OCTOBER 20, 2021

Data literacy is a key component for any organization to be able to scale responsible and trusted artificial intelligence technology. Achieving that level of governance at scale requires a common understanding of AI and data concepts. What Is Data Literacy? How Can Organizations Cultivate Data Literacy?

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

Domino Data Lab

AUGUST 5, 2019

This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. Data Scientists, Tradeoffs, and Data Ethics. As more companies become model-driven , data scientists are uniquely positioned to drive innovation and to help their companies remain economically strong.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

IBM Big Data Hub

OCTOBER 3, 2022

A large North American healthcare organization uses AI-infused data fabric architecture to help them identify vulnerable members who can benefit from timely intervention. What’s a data fabric and how is it different from a data mesh? . For many, part of the solution is trustworthy AI.

Machine Learning 52

Machine Learning Risk Insurance Cost-Benefit 52

IBM Big Data Hub

FEBRUARY 14, 2024

Assembling a version of the Mona Lisa in the style of Vincent van Gough is fun, but how often will that boost the bottom line? Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. We’re all amazed by what AI can do.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

CIO Business Intelligence

APRIL 29, 2022

Launching a data-first transformation means more than simply putting new hardware, software, and services into operation. True transformation can emerge only when an organization learns how to optimally acquire and act on data and use that data to architect new processes. Key features of data-first leaders.

Digital Transformation 132

Digital Transformation Strategy Data-driven Data Strategy 132

Insight

AUGUST 29, 2019

Insight Boston began its journey in 2015, with the first and only fellowship program dedicated to a career in Health Data Science. In 2017, we expanded the location to include our Data Science program, and in early 2018, we welcomed our first Data Engineering Fellows.

Data Science 56

Data Science Machine Learning Sales Measurement 56

Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. DATA FOR ENTERPRISE AI.

Digital Transformation 65

Digital Transformation Machine Learning Optimization Data Lake 65

Domino Data Lab

AUGUST 6, 2021

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. The complexity of models, and general limitations of expertise with data science among business leaders, creates an environment ripe for risk. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

DataRobot Blog

JULY 27, 2022

However, machine learning utilization is often unpredictable, which makes scaling sometimes a huge challenge. From our experience working with organizations across different industries, we learned about the main challenges related to this process. Data Science Expertise Meets Scalability.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

SEPTEMBER 27, 2022

Data and insights belong to their creator. IBM clients’ data is their data, and their insights are their insights. We believe that data policies should be fair and equitable and prioritize openness. Does it safeguard data? IBM Research has been developing trustworthy AI tools since 2012. Did anyone tamper with it?

Consulting 52

Consulting Machine Learning Modeling Strategy 52

Decision Management Solutions

DECEMBER 12, 2018

They had some great predictions and suggested priorities around the ethics of analytics, the value of data and the use of AI in fraud and cybersecurity. Plus most of the challenges with deploying AI are the same as those with analytics – check out this brief on How to Succeed with AI for our thoughts. Merge AI and Analytics.

Analytics 40

Analytics Predictive Analytics Modeling Data-driven 40

bridgei2i

FEBRUARY 6, 2020

AI has come a long way from Greek Mythology. AI has come a long way from Greek Mythology and Hollywood’s outlandish creative interpretations over the last few decades to becoming mainstream in a whole gamut of applications from autonomous cars, to facial recognition to smart speakers. Improving Operational Effectiveness. Digital Enterprise.

IoT 69

IoT Internet of Things Digital Transformation ROI 69

IBM Big Data Hub

JANUARY 10, 2023

Without a doubt, there is exponential growth in the access to and volume of process data we all, as individuals, have at our fingertips. Not only can data support a more compelling change management strategy, but it’s also able to identify, accelerate and embed change faster, all of which is critical in our continuously changing world.

Management 52

Management Data-driven Data mining Business Objectives 52

Sisense

JUNE 12, 2019

At Sisense, our mission is to empower users of all kinds with deep insights from even the most complex data. In addition, providing a world-class analytics platform requires a deep understanding of how to best leverage AI/ML to support the needs of all users from the novice to the most technical. Living in a World of Big Data.

Analytics 75

Analytics Data-driven Dashboards IoT 75

Insight

OCTOBER 25, 2019

Image credit: [link] As the title suggests, this is a story about a question that may resonate well with many machine learning practitioners trying to build applications in the real world, where clean and annotated data on a specific problem can be sparse— How do we leverage the power of AI when we have very little data?

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

CIO Business Intelligence

MAY 26, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. How can it be built? How can it be trained? But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems.

Machine Learning 145

Machine Learning Modeling Data-driven Enterprise 145

CIO Business Intelligence

MAY 28, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. How can it be built? How can it be trained? But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems.

Machine Learning 143

Machine Learning Modeling Data-driven Enterprise 143

Rocket-Powered Data Science

JULY 6, 2021

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade. 2) MLOps became the expected norm in machine learning and data science projects.

Machine Learning 279

Machine Learning Data-driven IoT Deep Learning 279

CIO Business Intelligence

FEBRUARY 28, 2024

It makes it challenging for organizations to operationalize generative AI,” says Anand Rao, AI professor at Carnegie Mellon University. The rate of companies that have either already deployed generative AI or are actively exploring it is accelerating to the point where, combined, there are very few holdouts. They need stability. in December.

IT 131

IT Consulting Modeling Enterprise 131

CIO Business Intelligence

APRIL 8, 2022

CIOs realize data is the new currency. But, if you can’t use your data as a differentiator to gain new insights, develop new products and services, enter new markets, and better meet the needs of existing ones, you’re not fully monetizing your data. Yesterday’s challenge: Lack of power, storage, and data.

Modeling 98

Modeling Machine Learning IoT Enterprise 98

IBM Big Data Hub

FEBRUARY 22, 2024

A recent IBM survey found that the top barriers preventing successful AI deployment include limited AI skills and expertise, data complexity, and ethical concerns. AI literacy is a must-have for security It’s important that personnel know how to deploy AI to improve organizational efficiencies.

Metadata 102

Metadata Measurement Risk Modeling 102

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. And ‘Mysterious meat stew’ included 500 grams of chopped human flesh.

Cost-Benefit 141

Cost-Benefit Manufacturing Machine Learning Experimentation 141

Sisense

AUGUST 21, 2020

AI and machine learning are the future of every industry, especially data and analytics. Reading through the Gartner Top 10 Trends in Data and Analytics for 2020 , I was struck by how different terms mean different things to different audiences under different contexts.

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. 42% of data scientists are solo practitioners or on teams of five or fewer people. 42% of data scientists are solo practitioners or on teams of five or fewer people.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

DataRobot Blog

SEPTEMBER 13, 2022

The future of business depends on artificial intelligence and machine learning. According to IDC , 83% of CEOs want their organizations to be more data-driven. Data scientists could be your key to unlocking the potential of the Information Revolution—but what do data scientists do? What Do Data Scientists Do?

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

Decision Management Solutions

JUNE 25, 2019

I presented on Backwards Engineering – planning Machine Learning (ML) deployment in reverse. Data shows that a traditional data-first approach to analytics is not generating much value for companies and I urged the audience instead to adopt a decisions-first mindset. I loved her three T’s – Trust, Teach, Technology.

Predictive Analytics 75

Predictive Analytics Analytics Data Science Experimentation 75

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. I would take a look at our Top Trends for Data and Analytics 2021 for additional AI, ML and related trends.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Cloudera

DECEMBER 13, 2022

How Agencies Can Gain the Cyber Edge with Smart Data Solutions. The question then, at the forefront of CISOs’ minds is, “How do you outpace the threats given the current IT estate?” The question then, at the forefront of CISOs’ minds is, “How do you outpace the threats given the current IT estate?”

Machine Learning 76

Machine Learning Experimentation Data Lake Data Processing 76

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. By simplifying Time Series Forecasting models and accelerating the AI lifecycle, DataRobot can centralize collaboration across the business—especially data science and IT teams—and maximize ROI.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Birst BI

JANUARY 29, 2019

How do you deliver more insights out to more people? Operationalizing BI and analytics – that is, putting the power of data in the hands of everyone across the enterprise, not just analysts and data scientists – has always been the mantra for Birst co-founder Brad Peters. Do you see the bottleneck?

Analytics 78

Analytics KPI Machine Learning Visualization 78

DataRobot

SEPTEMBER 14, 2021

As AI continues to advance at such an aggressive pace, solutions built on machine learning are quickly becoming the new norm. Data scientists and data engineers want full control over every aspect of their machine learning solutions and want coding interfaces so that they can use their favorite libraries and languages.

Machine Learning 94

Machine Learning Modeling Experimentation Visualization 94

DataRobot Blog

MARCH 23, 2023

This is why businesses are increasingly investing in machine learning operations (MLOps): IDC predicts by 2024, 60% of enterprises will have operationalized their ML workflows by using MLOps. 2 What Is MLOps and How Does It Help? 2 What Is MLOps and How Does It Help?

Machine Learning 52

Machine Learning Cost-Benefit Modeling Testing 52

Decision Management Solutions

AUGUST 13, 2020

Many of the projects we do these days involve helping clients operationalize machine learning (ML) or artificial intelligence (AI). We are often struck by how often the team working with this technology wants to use it for problems that are not a good fit. For instance, see this post on legacy modernization with rules.

Technology 80

Technology Digital Transformation Machine Learning Modeling 80

bridgei2i

JANUARY 25, 2022

How MLOps is Shaping AI in the Real World. How MLOps is Shaping AI in the Real World. PODCAST: Making AI Real. Listening time: 17 minutes. Tune in to the podcast to know more! Subscribe Now. Transcript. Shivalika: Hi there, you’re listening to the BRIDGEi2i podcast. And lucky for me, he’s not just my manager, but also my mentor.

Machine Learning 52

Machine Learning Modeling Data Processing Enterprise 52