Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

MARCH 18, 2020

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. Supervised learning is dominant, deep learning continues to rise. Respondent demographics. AI tools organizations are using.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

FEBRUARY 16, 2022

Given the complexity of some ML models, especially those based on Deep Learning (DL) Convolutional Neural Networks (CNNs), there are limits to interpretability. The comprehensive data governance features of the Shared Data Experience (SDX) provide strong data lineage controls and auditability.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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. . DVC — Open-source Version Control System for Machine Learning Projects … data version control.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

MARCH 22, 2022

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Sanjeev Mohan

SEPTEMBER 14, 2020

Oracle Autonomous database with AutoML, Google Cloud BigQuery ML, MS SQL Server and Cosmos DB with Spark integration and, Pivotal Greenplum with GPU- accelerated open-source deep learning library called Apache MADlib are only a few of the examples. The post Databases and Machine Learning Coalesce appeared first on Sanjeev Mohan.

Machine Learning 93

Machine Learning Data Warehouse Deep Learning Statistics 93

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 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

Domino Data Lab

JULY 2, 2019

Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Scale the problem to synthesize for hundreds of functions, and thousands of potential arguments. Software writes Software? With me so far?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Machine learning is not only appearing in more products and systems, but as we noted in a previous post , ML will also change how applications themselves get built in the future.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Domino Data Lab

JULY 9, 2019

” And using deep learning we can even go beyond that and we can say, “Here’s how editor number 12 is probably going to re-balance it,” versus, “Here’s…” You can actually learn different editor styles if you have enough data set. .” We crowdsourced it.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

IBM Big Data Hub

AUGUST 15, 2023

A common phrase you’ll hear around AI is that artificial intelligence is only as good as the data foundation that shapes it. Therefore, a well-built AI for business program must also have a good data governance framework. Doing so allows your organization the ability to scale with trust and transparency.

IT 80

IT Data Governance Modeling Cost-Benefit 80

CDW Research Hub

SEPTEMBER 15, 2020

They also aren’t built to integrate new technologies such as artificial intelligence and deep learning tools, which can move business to continuous intelligence and from predictive to prescriptive analytics. Easy Access with a Secure Foundation.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

O'Reilly on Data

JANUARY 7, 2020

In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products—and a majority of companies are starting to adopt machine learning. The line between data and AI is blurring. New models and methods are emerging.

Deep Learning 179

Deep Learning Machine Learning Experimentation Modeling 179