TDAN

AUGUST 6, 2019

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

Deep Learning 81

Deep Learning Technology Data Architecture Metadata 81

O'Reilly on Data

JANUARY 29, 2019

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. We found companies were planning to use deep learning over the next 12-18 months.

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. 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

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

CIO Business Intelligence

MARCH 9, 2022

If those in charge of managing the data lake don’t create precise processes and metadata for organizing data, the lake can quickly devolve into what’s come to be known as a “data swamp”—a data lake that makes it hard for users to locate data. . On the other hand, they don’t support transactions or enforce data quality.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Along with your database servers, you had, data warehousing and business intelligence. Then things changed. You can take TensorFlow.js

Data Science 109

Data Science Machine Learning Data Governance Modeling 109