Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. And the goodness doesn’t stop there.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

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. So let’s introduce Cloudera Machine Learning (CML) and discuss how it addresses the aforementioned silo issues.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

CIO Business Intelligence

MARCH 19, 2025

Mark Brooks, who became CIO of Reinsurance Group of America in 2023, did just that, and restructured the technology organization to support the platform, redefined the programs success metrics, and proved to the board that IT is a good steward of the dollar. One significant change we made was in our use of metrics to challenge my team.

Metrics 64

Metrics Enterprise Cost-Benefit Experimentation 64

Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. A playbook for this is to run multiple experiments in parallel and create ‘MVPs’ (fail/learn fast), as well as incorporate feedback mechanisms to enable an improvement loop, and scaling the ones that show the fastest path to ROI.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

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. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

NOVEMBER 15, 2022

Experiment with the “highly visible and highly hyped”: Gartner repeatedly pointed out that organisations that innovate during tough economic times “stay ahead of the pack”, with Mesaglio in particular calling for such experimentation to be public and visible. Artificial Intelligence, Digital Transformation, Innovation, Machine Learning

Digital Transformation 143

Digital Transformation Machine Learning Experimentation Metrics 143

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

Smart Data Collective

JULY 9, 2023

Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on. It is a crucial metric that provides priceless information about your website’s ability to transform visitors into paying customers. Some of the most important is conversion rates.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

CIO Business Intelligence

DECEMBER 19, 2024

In especially high demand are IT pros with software development, data science and machine learning skills. While crucial, if organizations are only monitoring environmental metrics, they are missing critical pieces of a comprehensive environmental, social, and governance (ESG) program and are unable to fully understand their impacts.

IT 52

IT IoT Machine Learning Optimization 52

CIO Business Intelligence

AUGUST 15, 2024

A virtual assistant may save employees time when searching for old documents or composing emails, but most organizations have no idea how much time those tasks have taken historically, having never tracked such metrics before, she says. There are a lot of cool AI solutions that are cheaper than generative AI,” Stephenson says.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

AWS Big Data

SEPTEMBER 5, 2024

Although the absolute metrics of the sparse vector model can’t surpass those of the best dense vector models, it possesses unique and advantageous characteristics. Experimental data selection For retrieval evaluation, we used to use the datasets from BeIR. We care more about the recall metric.

Metrics 109

Metrics Testing Experimentation Modeling 109

DataRobot Blog

OCTOBER 18, 2022

Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. Monitoring with Machine Learning. Learn How to Accelerate Business Results with DataRobot AI Cloud. DataRobot Booth at Big Data & AI Toronto 2022. Request a Demo.

Big Data 96

Big Data Forecasting Experimentation Machine Learning 96

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

CIO Business Intelligence

APRIL 12, 2024

Computer Vision also gives insights about customer traffic in stores, including metrics on conversion rate and sales numbers, thus helping the company decide what products to stock, how to display them, and how to arrange products across the store, Allison adds.

Experimentation 116

Experimentation Sales Digital Transformation Machine Learning 116

CIO Business Intelligence

JUNE 11, 2024

That definition was well ahead of its time and forecasted the current era’s machine learning and generative AI capabilities. What dataops, data governance, machine learning, and AI capabilities are IT developing as competitive differentiators?

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

IBM Big Data Hub

JUNE 10, 2024

XaaS models offer organizations greater predictability and transparency in cost management by providing detailed billing metrics and usage analytics. Accessing specialized expertise Implementing AI initiatives often requires specialized skills and expertise in areas such as data science, machine learning and AI development.

Experimentation 62

Experimentation Optimization Risk Management Machine Learning 62

Occam's Razor

MARCH 23, 2021

A key part of how this manifested in our work was doing truly super-advanced machine-learning powered analysis to answer hard questions that few can successfully. The benchmark for the beautiful metric AVOC is 15.3%. Now repeat this across many, many metrics, for many dimensions, in the three clusters you see above.

Analytics 133

Analytics Scorecard Strategy Testing 133

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 Data-driven Modeling 135

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 95

Analytics Metrics Strategy Measurement 95

AWS Big Data

AUGUST 21, 2023

In semantic search , the search engine uses a machine learning (ML) model to encode text from the source documents as a dense vector in a high-dimensional vector space; this is also called embedding the text into the vector space. Only items that have all or most of the words the user typed match the query.

Data Processing 98

Data Processing Visualization Experimentation Metrics 98

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Corinium

APRIL 25, 2019

Life insurance needs accurate data on consumer health, age and other metrics of risk. Machine learning can keep up, by continually looking for trends and anomalies, or predictive analytics, that are interesting for the given use case. And more recently, we have also seen innovation with IOT (Internet Of Things).

Insurance 150

Insurance Risk IoT Data-driven 150

Occam's Razor

FEBRUARY 28, 2017

To ensure customer delight was delivered in a timely manner, it was also decided that Average Call Time (ACT) would now be The success metric. The success metric, ACT, did go down. That ACT was an activity metric was terrible – if you have a The success metric, it should always be an outcome metric. Another issue.

Key Performance Indicator 107

Key Performance Indicator Metrics Measurement Advertising 107

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. AI Platform Single-Tenant SaaS are fully managed by DataRobot and replace disparate machine learning tools, simplifying management.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. The accuracy of machine learning models is highly dependent on the quality of the training data. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. They can enjoy a hosted experience with code snippets, versioning, and simple environment management for rapid AI experimentation.

Data Processing 72

Data Processing Experimentation Machine Learning Data Warehouse 72

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. About the Authors Eliad Gat is a Big Data & AI/ML Architect at Orca Security.

Data Lake 97

Data Lake Analytics Snapshot Data Quality 97

Cloudera

OCTOBER 8, 2024

By 2023, the focus shifted towards experimentation. Multiple AI Framework Support: Integrates seamlessly with popular machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers, making it easy to deploy a wide variety of model types.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

CIO Business Intelligence

APRIL 18, 2022

They also advise communicating the dashboard’s value consistently since that will drive effective dashboard use, both to increase adoption and to improve company performance on key dashboard metrics, the brief says. Given the nature of its business, Charles River is implementing cutting-edge technologies like AI and machine learning.

Digital Transformation 145

Digital Transformation Dashboards Cost-Benefit Consulting 145

AWS Big Data

JANUARY 9, 2024

2023 was a year of rapid innovation within the artificial intelligence (AI) and machine learning (ML) space, and search has been a significant beneficiary of that progress. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

Visualization 113

Visualization Cost-Benefit Modeling Machine Learning 113

DataRobot

JUNE 10, 2021

Traditionally, experimentation and observation was the only way to understand the physical-chemical properties of the molecule. If machine learning could contribute, this would allow for the faster invention of new compounds tailored for particular aromatic signatures.

Metrics 52

Metrics Machine Learning Visualization Experimentation 52

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 63

Experimentation Machine Learning Metrics Modeling 63