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Machine Learning in Oracle Database

Machine Learning in Oracle Database supports data exploration, preparation, and machine learning (ML) modeling at scale using SQL, R, Python, REST, automated machine learning (AutoML), and no-code interfaces. It includes more than 30 high performance in-database algorithms producing models for immediate use in applications. By keeping data in the database, organizations can simplify their overall architecture and maintain data synchronization and security. It enables data scientists and other data professionals to build models quickly by simplifying and automating key elements of the machine learning lifecycle.

Oracle introduce o bază de date vectoriale integrată pentru a consolida inteligența artificială generativă și pentru a spori considerabil productivitatea dezvoltatorilor

Noua căutare de similaritate vectorială AI în Oracle Database 23c permite combinarea căutării în baza de date semantice și de afaceri pentru a oferi răspunsuri foarte precise, rapid și sigur.

Machine Learning in Oracle Database customer successes

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UK NHS uses Machine Learning in Oracle Database to identify £1 billion in savings and provide better personalized care
Certegy helps businesses minimize losses and prevent fraud with Autonomous Database and Machine Learning in Oracle Database
Sensa Analytics improves payment reimbursement timelines and reduces accounts receivable outstanding by 39%
Forth Smart uses Machine Learning in Oracle Database to reduce costs and improve the effectiveness of targeted ads
BBVA achieves up to 40% improvement in click-through and conversion rates in marketing campaigns with Machine Learning in Oracle Database
NEOS uses Machine Learning in Oracle Database to execute predictive models faster and more accurately with better insights and advice to customers
September 19, 2023

Introducing natural language to SQL generation on Autonomous Database

Mark Hornick, Senior Director, Data Science and Machine Learning, Oracle

We’re pleased to announce Autonomous Database Select AI, a new capability that lets you query your data using natural language. Select AI combines generative AI with SQL so you can describe what you want—declarative intent—without specialized SQL knowledge and let the database generate the SQL query for you.

Read the complete post

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Machine Learning in Oracle Database reference architectures

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  • Reference Architecture

    With Oracle Autonomous Data Warehouse, you have all the necessary built-in tools to load and prepare data and to train, deploy, and manage machine learning models. You also have the flexibility to mix and match other tools to best fit your organization’s needs.

  • Reference Architecture

    Learn the design principles associated with creating a machine learning platform and an optimal implementation path. Use this pattern to create machine learning platforms that meet the needs of your data scientist users.

  • Reference Architecture

    Get the framework to enrich enterprise application data with raw data from other sources, and then use machine learning models to bring intelligence and predictive insights into business processes.

  • Reference Architecture

    Discover the platform topology, component overview, and recommended best practices for implementing a successful data lakehouse on OCI to capture a wealth of data and aggregate and manage data for real-time stock visibility.

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