O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. However, the concept is quite abstract.

IT 364

IT Testing Experimentation Software 364

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Collaboration and Sharing.

Testing 300

Testing Machine Learning Consulting Data Science 300

AWS Big Data

JANUARY 15, 2025

Improve accuracy and resiliency of analytics and machine learning by fostering data standards and high-quality data products. In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications.

IoT 101

IoT Machine Learning Metadata Data-driven 101

Corinium

JUNE 6, 2019

A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment. It is also important to have a strong test and learn culture to encourage rapid experimentation. Build multiple MVPs to test conceptually and learn from early user feedback.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. While useful, these constructs are not beyond criticism.

Management 314

Management Machine Learning Metrics Modeling 314

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. blueberry spacing) is a measure of the model’s interpretability. Machine Learning Model Lineage. Machine Learning Model Visibility . Figure 04: Applied Machine Learning Prototypes (AMPs).

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

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) Industry 4.0

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

JUNE 14, 2023

Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. If you’re looking to get an edge on a data analytics career, certification is a great option. The number of data analytics certs is expanding rapidly.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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

DECEMBER 19, 2024

In especially high demand are IT pros with software development, data science and machine learning skills. This is where machine learning algorithms become indispensable for tasks such as predicting energy loads or modeling climate patterns.

IT 52

IT IoT Machine Learning Optimization 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

CIO Business Intelligence

AUGUST 15, 2024

Meanwhile, “traditional” AI technologies in use at the time, including machine learning, deep learning, and predictive analysis, continue to prove their value to many organizations, he says. He also advises CIOs to foster a culture of continuous learning and upskilling to build internal AI capabilities.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

JANUARY 28, 2025

This transition represents more than just a shift from traditional systemsit marks a significant pivot from experimentation and proof-of-concept to scaled adoption and measurable value. According to Jyoti, AI and machine learning are leading the way in sectors such as government, healthcare, and financial services.

Digital Transformation 52

Digital Transformation Data-driven Experimentation Strategy 52

CIO Business Intelligence

JULY 7, 2023

A security-by-design culture incorporates security measures deeply into the design and development of systems, rather than treating them as an afterthought. They are expected to make smarter and faster decisions using data, analytics, and machine learning models. Caution is king, however.

Measurement 122

Measurement Risk Experimentation Enterprise 122

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

DataRobot

JULY 27, 2021

Last fall, I penned a blog post around our Series F funding, focused on the fact that the era of experimental AI is over. AI needs to be a core part of every company’s strategy and culture, as well as a top company initiative with a focus on measurable results tied to value. . I stand by that notion wholeheartedly.

Machine Learning 98

Machine Learning Experimentation Modeling Forecasting 98

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. A sure-fire formula for driving innovative growth is to “try something new, learn fast, pivot as needed, and scale success,’’ says Mike Crowe, CIO of Colgate-Palmolive. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

datapine

JANUARY 31, 2022

For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. The results?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

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? Without this data, it’s risky for CIOs to take on a rebranding effort.

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

Smart Data Collective

JULY 9, 2023

Optimizing Conversion Rates with Data-Driven Strategies A/B Testing and Experimentation for Conversion Rate Optimization A/B testing is essential for discovering which version of your website’s elements are most effective in driving conversions. Experimentation is the key to finding the highest-yielding version of your website elements.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

Insight

FEBRUARY 20, 2020

Only Bias Understanding why noise in machine learning is nothing but bias In this post, we explain how bias and noise in machine learning are two sides of the same coin. Read on to see how the same goes for the fundamental laws of machine learning. There is No Noise?—?Only God does not play dice.?—?Albert

Machine Learning 71

Machine Learning Experimentation Modeling Measurement 71

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. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

APRIL 18, 2022

Tech leaders “should have a common language that clearly defines their company’s digital imperatives, with related value measures, that allows the organization to align on strategy across the C-suite and to communicate the strategic value they hope to achieve from it,” Nanda says. They invest in cloud experimentation.

Digital Transformation 145

Digital Transformation Dashboards Cost-Benefit Consulting 145

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

SEPTEMBER 5, 2024

Experimental data selection For retrieval evaluation, we used to use the datasets from BeIR. To mimic the knowledge retrieval scenario, we choose BeIR/fiqa and squad_v2 as our experimental datasets. Based on our experience of RAG, we measured recall@1, recall@4, and recall@10 for your reference.

Metrics 106

Metrics Testing Experimentation Modeling 106

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AutoML tools: Automated machine learning, or autoML, supports faster model creation with low-code and no-code functionality.

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

CIO Business Intelligence

APRIL 26, 2023

“This creates a culture of ‘ladder-climbing’ rather than a focus on continuous training, learning, and improvement,” says Nicolás Ávila, CTO for North America at software development firm Globant. Ensure there’s an ability to measure training effectiveness during and after the training program’s completion.”

IT 105

IT Experimentation Forecasting Machine Learning 105

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

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 97

Data Processing Visualization Experimentation Metrics 97

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. This functionality was initially released as experimental in OpenSearch Service version 2.4, and is now generally available with version 2.9.

Visualization 107

Visualization Cost-Benefit Modeling Machine Learning 107

CIO Business Intelligence

OCTOBER 9, 2023

Hyatt’s experimental mindset and listen-first approach are heavily applied to IT’s pursuit of innovation, he says. I think of it almost like a machine learning algorithm called ‘multi-armed bandit,’” that has two axes: exploit and explore, he says. Innovation, IT Leadership, IT Operations, IT Strategy

Strategy 137

Strategy Technology Experimentation Testing 137

DataRobot

APRIL 29, 2021

Eric Weber is Head of Experimentation And Metrics for Yelp. He is putting his expertise in machine learning and web analytics to use for the thriving online retailer. Rayid Ghani is a Professor at Carnegie Mellon University where he is focused on using machine learning to drive improved public policy decisions.

Machine Learning 59

Machine Learning Experimentation Data Science Data-driven 59

DataRobot

JUNE 17, 2021

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. This search for mathematical formulas makes Eureqa different from other machine learning algorithms. So What is Eureqa?

Modeling 52

Modeling Experimentation Machine Learning Measurement 52

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Ask them what they worry about, ask them what they are solving for, ask them how they measure success, ask them what are two things on the horizon that they are excited about.

Marketing 138

Marketing Analytics Machine Learning Strategy 138

Cloudera

OCTOBER 8, 2024

By 2023, the focus shifted towards experimentation. Enterprise-Grade Security: Implements robust security measures, including authentication, authorization*, and data encryption, helping ensure that data and models are protected both in transit and at rest. These innovations pushed the boundaries of what generative AI could achieve.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

Occam's Razor

FEBRUARY 28, 2017

The qualitative surveys measuring unhappiness went down even more than before. You are what you measure. Throw in Machine Learning and I weep at how many glorious sales, marketing, deep relationships initiatives are impossible because companies have not solved identity. The success metric, ACT, did go down.

Key Performance Indicator 107

Key Performance Indicator Metrics Measurement Advertising 107