This session was presented at Oracle Cloud Summit Virtual 2025.

Oracle’s AI capabilities for finance provides a collection of AI–and ML–based tools and capabilities to help improve operational efficiency, automate standard transactions, better predict business outcomes, and optimize cash flow. Auto-predictive planning, Predictive cash forecasting, AutoML for custom models are some of the out of features which helps to take "Data-Driven Predictions" for effective decisions. AI helps to perform "Touchless Operations" like Transaction matching (automate high-volume, labor-intensive, and complex reconciliations) and Generated content in narrative reporting (Generate narrative and insights in reports based on data) It also offers "Digital assistance" to Interact with your EPM data. This session is going to talk about all AI driven features in EPM which helps users to take effective decisions. For review - This session must attend session for all EPM Practitioners and customers to know more about the Oracle’ AI offering in EPM. This session is in align with Oracle long term strategy in which AI should be driving factor to take effective decisions by Customer. Will spread awareness about AI features available in EPM tools.

Presented at RECONNECT Dive Deep 2021

Session ID: 101930

Join Pratap Madgula, Director of Innovation and Implementation at Kaiser Permanente, to hear about emerging technologies like RPA, chatbots, machine learning, AI, and Oracle Analytics Cloud Services and how Kaiser Permanente utilizes them.

Presented at Database & Technology Week 2021

Using data to gain insights, make predictions, and identify patterns has become a priority for most enterprises. Machine learning is a key technology, but it often requires specific skill sets to take advantage of. Even for experts, the machine learning process can be highly iterative and involve significant trial and error. To help make machine learning more accessible to a broader set of users and enhance data scientist productivity, Oracle introduced automated machine learning, or AutoML, both from a Python API and a no-code user interface. In this session, we introduce the machine learning process and how AutoML plays a key role in the modeling process. We’ll include a demonstration of the no-code OML AutoML UI and the OML4Py AutoML features.

Presented at Database & Technology Week 2021

This presentation will focus on what specific algorithms inside Oracle can be applied to business problems. Robots may be the first to truly learn machine learning (ML) and expand into artificial intelligence (AI). Python is one of the keys to machine learning as we program the invention of the mind to further replace humans’ most basic tasks. This session will focus on ML 101 and building the future ahead. Some business issues are seasonal, some relate to customers with certain attributes, and some relate to customers we don’t know exist, but all can be solved by using the correct algorithm to quickly prescribe a better corporate future.

Presented at INSYNC 21

Session ID: 101960

In-database machine learning offers automation, scalability, and ease of deployment. With the arrival of 21c, there are a few new "faces" to Oracle Machine Learning (OML) to take you further in your data science projects. OML on Autonomous Database introduces a Python API, a no-code AutoML user interface, and a database-external model deployment REST interface. With OML for Python, data scientists leverage the database as a high-performance data science compute engine - minimizing data movement - as well as benefit from powerful automated machine learning. OML AutoML UI places a no-code user interface in the hands of data scientists and non-expert users as a productivity tool to automate the modeling and deployment process. OML Services provides REST endpoints for model management and deployment along with cognitive text analytics. Join us for this OML overview with demonstrations.

Presented at INSYNC 21

Session ID: 101380

Oracle Machine Learning’s new AutoML UI makes ML easier than ever before.  OML’s AutoML automates many of the time-intensive and repetitive aspects of a data scientist’s job including algorithm selection, feature selection, and hyperparameter tuning.  AutoML UI enables “citizen data scientists” to leverage AutoML in ADW with a simple, intuitive, easy to use UI.   Using AutoML UI, data scientists and citizen data scientists can focus on the important phases of ML: Defining the problem, assembling the “right data”, disseminating the model’s insights and predictions, and deploying the model enterprise-wide.  Come see the new AutoML UI and learn how easy it is to get started.

Presented at INSYNC 21

Session ID: 101970

In this Hands-on Lab, join us to experience Oracle Machine Learning for Python (OML4Py) on Oracle Autonomous Database. OML4Py supports scalable, in-database data exploration and preparation using native Python syntax, invocation of in-database algorithms for model building and scoring, and embedded execution of user-defined Python functions from Python or REST APIs. OML4Py also includes the AutoML interface for automated algorithms, feature selection, and hyperparameter tuning. In this six-part lab, explore the range of Python-enabled functionality and see how Oracle technology can support your data science projects.