Remove Data Governance Remove Data Integration Remove Deep Learning Remove Measurement
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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. We found companies were planning to use deep learning over the next 12-18 months. On the other hand, we wanted to measure the sophistication of their use of these components.

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Core technologies and tools for AI, big data, and cloud computing

O'Reilly on Data

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. AI and machine learning in the enterprise. Deep Learning. Foundational data technologies.

Big Data 209
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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

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.

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The DataOps Vendor Landscape, 2021

DataKitchen

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. . QuerySurge – Continuously detect data issues in your delivery pipelines. Process Analytics. Azure DevOps.

Testing 300
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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

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
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How to choose the best AI platform

IBM Big Data Hub

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.