O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. It’s a very simple and powerful idea: simulate data that you find interesting and see what a model predicts for that data. 6] Debugging may focus on a variety of failure modes (i.e.,

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

JUNE 2, 2022

Specifically, they are interested in electric utility response to cyber and physical threats, and they are working to develop an algorithm that can be used as a tested, trusted safeguard. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Informatics 86

Informatics Modeling Testing Technology 86

CIO Business Intelligence

APRIL 4, 2022

Find out more and take a test drive in one of Dell Technologies’ worldwide Customer Solution Centers. Data analytics is the key to unlocking the most value you can extract from data across your organization. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Technology 52

Technology Deep Learning Cost-Benefit Data Quality 52

DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataKitchen

APRIL 13, 2021

Testing and Data Observability. 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. . Genie — Distributed big data orchestration service by Netflix.

Testing 300

Testing Machine Learning Consulting Data Quality 300

O'Reilly on Data

MARCH 31, 2020

The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 333

Management Machine Learning Experimentation Metrics 333

O'Reilly on Data

JUNE 19, 2019

More precisely, models built or tuned for specific applications (in reality, this means models + data ) will need to be managed and protected : A database for authorization and security: who has read/write access to certain models. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Modeling 193

Modeling Machine Learning Testing Metrics 193

Smarten

APRIL 19, 2024

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

JUNE 23, 2019

Be aware that machine learning often involves working on something that isn’t guaranteed to work. As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. Testing is critical. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

DataRobot Blog

DECEMBER 15, 2022

If your dataset is not in time order (time consistency is required for accurate Time Series projects), DataRobot can fix those gaps using the DataRobot Data Prep tool , a no-code tool that will get your data ready for Time Series forecasting. Prepare your data for Time Series Forecasting.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Domino Data Lab

MARCH 3, 2019

I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms. Companies are building data infrastructure in the cloud: 85% indicated they have data infrastructure in at least one cloud provider. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

DataRobot Blog

DECEMBER 20, 2022

In this article, we’ll first take a closer look at the concept of Real Estate Data Intelligence and the potential of AI to become a game changer in this niche. We’ll then empirically test this assumption based on an example of real estate asset assessment. You can understand the data and model’s behavior at any time.

Management 59

Management Machine Learning Optimization Modeling 59

O'Reilly on Data

MARCH 24, 2020

However, attempting to repurpose pre-existing data can muddy the water by shifting the semantics from why the data was collected to the question you hope to answer. ” One of his more egregious errors was to continually test already collected data for new hypotheses until one stuck, after his initial hypothesis failed [4].

Machine Learning 347

Machine Learning Statistics Data Quality Modeling 347