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

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

JANUARY 24, 2025

In bps case, the multiple generations of IT hardware and software have been made even more complex by the scope and variety of the companys operations, from oil exploration to electric vehicle (EV) charging machines to the ordinary office activities of a corporation.

Digital Transformation 59

Digital Transformation B2B Testing Experimentation 59

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

MARCH 19, 2025

I first described the overall AI landscape and made sure they realized weve been doing AI for quite a while in the form of machine learning and other deterministic models. An Agile and product management mindset is also necessary to foster an experimentation approach, and to move away from the desire to control data.

Metrics 65

Metrics Enterprise Cost-Benefit Experimentation 65

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ).

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

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

It comes in two modes: document-only and bi-encoder. For more details about these two terms, see Improving document retrieval with sparse semantic encoders. Simply put, in document-only mode, term expansion is performed only during document ingestion. Bi-encoder mode improves performance but may cause more latency.

Metrics 110

Metrics Testing Experimentation Modeling 110

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. Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

Visualization 116

Visualization Cost-Benefit Modeling Machine Learning 116

AWS Big Data

AUGUST 21, 2023

Lexical search looks for words in the documents that appear in the queries. Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. OpenSearch Service supports a variety of search and relevance ranking techniques.

Data Processing 98

Data Processing Visualization Experimentation Metrics 98

Domino Data Lab

FEBRUARY 12, 2020

for reinforcement learning (RL), ? for model serving (experimental), are implemented with Ray internally for its scalable, distributed computing and state management benefits, while providing a domain-specific API for the purposes they serve. Motivations for Ray: Training a Reinforcement Learning (RL) Model. multiprocessing , ?

Experimentation 137

Experimentation Modeling Data Science Machine Learning 137

Cloudera

OCTOBER 18, 2023

Historically, firms have relied on high-cost, third-party solutions to help identify savings opportunities, however, the landscape is rapidly changing, and the emergence of AI and machine learning (ML) has ushered in a new era of possibilities. Automated documentation generation: Generating documentation is time consuming and tedious.

Cost-Benefit 79

Cost-Benefit Testing Machine Learning Optimization 79

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. And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. Becoming AI-driven is no longer really optional. Request a Demo.

Machine Learning 94

Machine Learning Experimentation Modeling Visualization 94

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

CIO Business Intelligence

APRIL 24, 2024

That includes many technologies based on machine learning, such as sales forecasting, lead scoring and qualification, pricing optimization, and customer sentiment analysis. This brings in intelligence from all the data, and from unstructured documents, so for an individual, we can answer the questions they need answered.”

Sales 128

Sales Finance Experimentation Cost-Benefit 128

CIO Business Intelligence

APRIL 15, 2024

Tax preparation company H&R Block is no stranger to AI and machine learning (ML), having leveraged the technologies across its business for years. Given the speed required, Lowden established a specialized team for the project to encourage a culture of experimentation and “moving fast to learn fast.” “You

Testing 102

Testing Machine Learning Data Quality Experimentation 102

AWS Big Data

MAY 2, 2023

Removal of experimental Smart Sensors. For detailed release documentation with sample code, visit the Apache Airflow v2.4.0 This feature is particularly useful if you want to externally process various files, evaluate multiple machine learning models, or extraneously process a varied amount of data based on a SQL request.

Testing 124

Testing Experimentation Management Metadata 124

DataRobot Blog

NOVEMBER 15, 2022

At the event, a financial services panel discussion shared why iteration and experimentation are critical in an AI-driven data science environment. With DataRobot , Sara has the ability to explain the models that her Data Science team is creating and can automatically generate the required compliance documentation.

Big Data 52

Big Data Experimentation Machine Learning Data-driven 52

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

Domino Data Lab

JULY 2, 2019

Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively? The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. of relational databases represent early forms of machine learning.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

MAY 30, 2024

After this project, we’ll constantly introduce AI on other sectors and services like control of travel documentation.” I’ve given colleagues the freedom to do research and experimentation together with our automation partner Mauden,” says Ciuccarelli. “We AI is the future for us,” says Maffei.

Cost-Benefit 120

Cost-Benefit Sales Modeling Experimentation 120

DataRobot Blog

FEBRUARY 9, 2022

Machine learning operations (MLOps) solutions allow all models to be monitored from a central location, regardless of where they are hosted or deployed. Manual processes cannot keep up with the speed and scale of the machine learning lifecycle , as it evolves constantly. Implement MLOps Tools.

IT 52

IT Experimentation Machine Learning Data Processing 52

DataRobot

JUNE 23, 2021

To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. This allows data science teams to incorporate any machine learning algorithm or feature engineering method and seamlessly combine them with hundreds of built-in methods. Run AutoPilot.

Machine Learning 52

Machine Learning Visualization Experimentation Modeling 52

Sanjeev Mohan

FEBRUARY 6, 2019

I saw the winds change and the inquiry requests shifted towards advanced analytics involving machine learning (ML) questions. I ended up writing two documents on data governance. To address client questions about cloud, I wrote a document on GCP. That’s where the bulk of my time was spent.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Domino Data Lab

AUGUST 6, 2021

The process of doing data science is about learning from experimentation failures, but inadvertent errors can create enormous risks in model implementation. Doing the practical aspects of implementation and ongoing monitoring of risk requires the use of a software solution called Enterprise Machine Learning Operations (MLOps).

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Cloudera

OCTOBER 8, 2024

By 2023, the focus shifted towards experimentation. Detailed Data and Model Lineage Tracking*: Ensures comprehensive tracking and documentation of data transformations and model lifecycle events, enhancing reproducibility and auditability. These innovations pushed the boundaries of what generative AI could achieve.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

Cloudera

MAY 31, 2023

This approach combines generative capabilities with the ability to retrieve information from your knowledge base using vector databases like Milvus populated with your documents. Cloudera Machine Learning (CML) is one of these data services provided in CDP.

Enterprise 74

Enterprise Data Processing Machine Learning Experimentation 74

IBM Big Data Hub

MARCH 27, 2024

The Eora MRIO (Multi-region input-output) dataset is a globally recognized spend-based emission factor set that documents the inter-sectoral transfers amongst 15.909 sectors across 190 countries. The experimental results indicate that fine-tuned LLMs exhibit significant improvements over the zero-shot classification approach.

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

DataRobot Blog

JANUARY 12, 2023

trillion predictions for customers around the globe, DataRobot provides both a strong machine learning platform and unique data science services that help data-driven enterprises solve critical business problems. Delivering more than 1.4 Benefits of Seamless DataRobot AI and Google Cloud Services Integration.

Management 59

Management Data-driven ROI Data Science 59

Domino Data Lab

AUGUST 6, 2021

When you factor in the requirements of a business-critical machine learning model in a working enterprise environment, the old cat-herding meme won’t even get a smile. Develop: includes accessing and preparing data and algorithms, researching and development of models and experimentation. 4 Steps in the DSLC.

Data Science 75

Data Science Testing Modeling Publishing 75

CIO Business Intelligence

JUNE 28, 2023

Many CIOs have become the de facto generative AI professor and spent ample time developing 101 materials and conducting roadshows to build awareness, explain how generative AI differs from machine learning, and discuss the inherent risks. Experimentation with a use case driven approach. Looking forward.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

Cloudera

NOVEMBER 25, 2020

For example, it includes patient samples (blood, blood pressure, temperature, and more), patient information (age, gender, where they have lived, family situation, and other details), and treatment history, most of which is currently found only in paper documents. Matthew’s company is not alone in this situation.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

Domino Data Lab

AUGUST 22, 2019

Common natural language preprocessing options include: Tokenization: This is the splitting of a document (e.g., Execute gutenberg.fileids() to print the names of all 18 documents.) As we wrap up the section later on, we’ll apply the steps across the entire 18-document corpus. Journal of Machine Learning Research, 9, 2579–605.].

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

DataRobot Blog

SEPTEMBER 30, 2022

How do you track the integrity of a machine learning model in production? Adoption of AI/ML is maturing from experimentation to deployment. Learn more about DataRobot MLOps and access public documentation to get more technical details about recently released features. Model Observability can help. Request a demo.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

AWS Big Data

JULY 26, 2023

The vector engine provides a simple, scalable, and high-performing similarity search capability in Amazon OpenSearch Serverless that makes it easy for you to build modern machine learning (ML) augmented search experiences and generative artificial intelligence (AI) applications without having to manage the underlying vector database infrastructure.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

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. Code (62%) : Gen AI helps developers write code more efficiently and with fewer errors.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

Domino Data Lab

DECEMBER 4, 2020

Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). 2] Pumas AI Documentation, [link]. [3] The Domino data science platform empowers data scientists to develop and deliver models with open access to the tools they love. References. [1]

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59