Smart Data Collective

OCTOBER 13, 2022

These patterns could then be used as the basis for additional experimentation by scientists or engineers. Generative design is a new approach to product development that uses artificial intelligence to generate and test many possible designs. Automated Testing of Features. Generative Design. Quality Assurance.

Testing 114

Testing Cost-Benefit Experimentation Optimization 114

DataKitchen

APRIL 13, 2021

Testing and Data Observability. Sandbox Creation and Management. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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

Domino Data Lab

MAY 15, 2019

It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev. I was fortunate to see an early iteration of Pete Skomoroch ’s ML product management presentation in November 2018.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

CIO Business Intelligence

JANUARY 19, 2024

Data science certifications give you an opportunity to not only develop skills that are hard to find in your desired industry, but also validate your data science know-how so recruiters and hiring managers know what they get if they hire you. The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Domino Data Lab

MARCH 20, 2019

Our mission at Domino is to enable organizations to put models at the heart of their business. Today we’re announcing two major new capabilities in Domino that make model development easier and faster for data scientists. see the Domino Support site and watch this tutorial: Domino Experiment Manager. Domino Datasets.

Management 97

Management Experimentation Data Science Modeling 97

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 126

Experimentation Strategy Machine Learning Interactive 126

CIO Business Intelligence

MARCH 12, 2024

Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others. Gen AI is also reducing the time needed to complete testing, via automation, Ramakrishnan says.

Software 131

Software Experimentation Testing Cost-Benefit 131

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch presented “ Product Management for AI ” at Rev. 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. Session Summary. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

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

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Develop/execute regression testing . Test data management and other functions provided ‘as a service’ . Agile ticketing/Kanban tools. Deploy to production.

Metrics 243

Metrics Experimentation Measurement Testing 243

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

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 We’re using our own databases, testing against our own needs, and building around specific problem sets.

Enterprise 114

Enterprise Experimentation Modeling Data-driven 114

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This simulation is based on the actual user network of GCP.

Testing 58

Testing Experimentation Measurement Modeling 58

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. The exam consists of 65 multiple-choice or multiple-response questions, which the candidate has 180 minutes to complete.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

NOVEMBER 7, 2022

A developing playbook of best practices for data science teams covers the development process and technologies for building and testing machine learning models. 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

CIO Business Intelligence

FEBRUARY 21, 2024

So students should learn about how to use the technology, and how to manage teams that use the tools — especially engineering teams. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We We’ve done a lot of experimentation on these adaptive tools that use AI,” says Ventimiglia.

Recreation/Entertainment 131

Recreation/Entertainment Experimentation Modeling Data-driven 131

Cloudera

OCTOBER 18, 2023

In fact, some of the insights presented in this blog have been assisted by the power of large language models (LLMs), highlighting the synergy between human expertise and AI-driven insights. Portfolio Optimization Analyze a portfolio of investments and identify opportunities to optimize returns while managing risk.

Cost-Benefit 77

Cost-Benefit Testing Machine Learning Optimization 77

CIO Business Intelligence

MARCH 10, 2022

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.” Z as a service.

Sales 128

Sales Testing Experimentation Data Processing 128

Domino Data Lab

OCTOBER 14, 2020

We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield. For example, our models can show farmers how to increase their production while using less fertilizer.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

CIO Business Intelligence

MARCH 7, 2023

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

Enterprise 115

Enterprise IT Experimentation Unstructured Data 115

DataKitchen

OCTOBER 5, 2021

DataOps enables: Rapid experimentation and innovation for the fastest delivery of new insights to customers. The Innovation Pipeline includes analytics development, QA, deployment and the rest of the change management processes for the Value Pipeline. The data scientist’s products are models and segmentations. Create tests.

Testing 152

Testing Dashboards Measurement Experimentation 152

CIO Business Intelligence

JUNE 28, 2023

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 94

Digital Transformation Cost-Benefit Informatics Data mining 94

Domino Data Lab

NOVEMBER 14, 2019

Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. Yet there are tradeoffs to consider when selecting a model. Errors like these may occur when the model is being constructed.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

NOVEMBER 13, 2023

Because of this, IT leaders must take a proactive approach to change management , communicating the benefits of digital transformation and providing support and training to employees. Foster a culture of innovation: Digital transformation requires innovation and experimentation, and thus a culture for embracing new technologies and ideas.

Digital Transformation 142

Digital Transformation Cost-Benefit Experimentation Measurement 142

CIO Business Intelligence

JULY 6, 2022

trillion in assets under management, another $46 trillion in assets under custody, and more than $307 billion in private wealth. Technology is always evolving, and we have to evolve with it and continue to manage it professionally. Because when you can experiment, you can potentially enter a new business quickly, test an idea.

Experimentation 93

Experimentation Testing Strategy Risk 93

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

Occam's Razor

AUGUST 12, 2013

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 161

Modeling Optimization Marketing Interactive 161

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. The main use of business intelligence is to help business units, managers, top executives, and other operational workers make better-informed decisions backed up with accurate data.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataKitchen

JANUARY 17, 2022

The company invested significant effort into managing lists of potential prescribers for certain drugs and treatments. However, the BA team spent most of its time overcoming error-prone data and managing fragile and unreliable analytics pipelines. . Testing and validating analytics took as long or longer than creating the analytics.

Experimentation 130

Experimentation Data Lake Marketing Predictive Modeling 130

Corinium

JUNE 6, 2019

Moreover, rapid and full adoption of analytics insights can hit speed bumps due to change resistance in the ways processes are managed and decisions are made. Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. Just don't fall for their bashing of all other vendors or their silly claims, false, of "superiority" in terms of running 19 billion combinations of tests or the bonus feature of helping you into your underwear each morning. And I meant every word of it.

Testing 112

Testing Experimentation Risk Optimization 112

AWS Big Data

JANUARY 9, 2024

Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Semantic search In semantic search, the search engine uses an ML model to encode text or other media (such as images and videos) from the source documents as a dense vector in a high-dimensional vector space.

Cost-Benefit 91

Cost-Benefit Visualization Modeling Machine Learning 91

DataRobot

SEPTEMBER 22, 2021

You have to pick the right model to meet expected performance goals. Train it, test it, tune it. You have to know how to take your model into production, manage it over time, enable the business to consume predictions from it, and use it to make the right decisions. You have to make your AI explainable and trustworthy.

Experimentation 85

Experimentation Testing Modeling Machine Learning 85

IBM Big Data Hub

DECEMBER 14, 2023

Another year has passed—it felt like the whole world was talking about and trying out tools powered by generative AI and Large Language Models (LLMs). Projects are a named collection of configurations that are used to manage related resources and Infrastructure as Code (IaC) deployments. Automated regression tests are a dynamite.

Experimentation 74

Experimentation Testing Software Management 74

AWS Big Data

AUGUST 21, 2023

For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. If you are interested in exploring the multi-modal model, please reach out to your AWS specialist. With OpenSearch’s Search Comparison Tool , you can compare the different approaches.

Data Processing 90

Data Processing Experimentation Visualization Metrics 90