O'Reilly on Data

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. 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

Insight

SEPTEMBER 20, 2019

The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. Discussion In this project, I used deep learning techniques to automatically detect lesion regions and classify the lesion, which can have both cost and time-saving benefits. The testing accuracy of the model is 0.79

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). 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.

Management 332

Management Machine Learning Experimentation Metrics 332

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

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. In short, the virtuous cycle is growing.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 Quality 300