O'Reilly on Data

FEBRUARY 4, 2019

As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for. To that end, we also asked respondents what technologies (open source, managed services) they use for things like data storage, data management, and data processing. Data Platforms.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

CIO Business Intelligence

JUNE 13, 2022

As with all financial services technologies, protecting customer data is extremely important. In some parts of the world, companies are required to host conversational AI applications and store the related data on self-managed servers rather than subscribing to a cloud-based service. Just starting out with analytics?

Data Processing 95

Data Processing Deep Learning Insurance Cost-Benefit 95

O'Reilly on Data

DECEMBER 12, 2019

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. Privacy harms : models can compromise individual privacy in a long (and growing) list of ways. [8]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. We keep feeding the monster data. We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

NOVEMBER 14, 2023

Additionally, by managing the data product as an isolated unit it can have location flexibility and portability — private or public cloud — depending on the established sensitivity and privacy controls for the data. Doing so can increase the quality of data integrated into data products.

Strategy 113

Strategy Cost-Benefit Data-driven Measurement 113

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. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 79

Machine Learning Manufacturing Cost-Benefit Deep Learning 79