Insight

SEPTEMBER 20, 2019

Segmentation Since a few patients had multiple images in the dataset, the data were separated, by patient, into three parts: training (80%), validation (10%), and testing (10%). The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. The box plot below shows a summary of the testing results.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

CIO Business Intelligence

JANUARY 23, 2023

The company has been a supporter of OpenAI’s quest to build an artificial general intelligence since its early days, beginning with its hosting of OpenAI experiments on specialized Azure servers in 2016. That app, Microsoft Designer , is currently in closed beta test.

Enterprise 131

Enterprise Deep Learning Recreation/Entertainment Interactive 131

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. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CDW Research Hub

JULY 31, 2019

Level 5 and beyond : at this level, contextual assistants are able to monitor and manage a host of other assistants in order to run certain aspects of enterprise operations. Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

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. . Testing and Data Observability. Production Monitoring and Development Testing.

Testing 300

Testing Machine Learning Consulting Data Quality 300

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Managing Machine Learning Projects” (AWS).

Management 332

Management Machine Learning Experimentation Metrics 332

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. Does machine learning change priorities?

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84