No results found

Your search did not match any results.

We suggest you try the following to help find what you’re looking for:

  • Check the spelling of your keyword search.
  • Use synonyms for the keyword you typed, for example, try “application” instead of “software.”
  • Try one of the popular searches shown below.
  • Start a new search.
Trending Questions
Oracle Developer Live

AI and ML for Your Enterprise


Join us for technical sessions, hands-on labs, demos, panels, and live Q&A with experts.

Register today.

Oracle Developer Live: AI and ML for Your Enterprise

Put AI to work for your business and IT operations. AI can accelerate automation, reduce human errors, and enhance business insights. Join Oracle executives and product experts as they discuss how to eliminate the development roadblocks to building an AI-powered enterprise. Because data is the foundation for AI, you'll also learn how to access, prepare, and process it with speed and agility.

Attend Oracle Developer Live to discover how you can optimize the data and machine learning lifecycle and spur AI adoption—all while delivering innovation, automation, and smarter decision making to your business.

Agenda

Times shown in

Welcome and Keynote: The Future of AI and ML—How AI Can Help Your Business

AI and machine learning are often hyped as the future of everything. So why is it such a challenge to apply AI to your specific business requirements? This keynote will consider how the world of AI services is likely to develop over the next few years and how Oracle is making it easier for AI to work for you.

  • Elad Ziklik

    Vice President, Product Management, AI Services and Data Science, Oracle

  • Manisha Gupta

    Senior Director, Product Management, Analytics Apps for HCM, Oracle

Accelerating Data Science Using the Oracle Accelerated Data Science SDK

This session provides an overview of the Oracle Accelerated Data Science (ADS) SDK, a Python library available through the OCI Data Science notebook session resource. The ADS SDK provides a series of tools and features that cover the entire lifecycle of machine learning models—from data acquired through a variety of sources and formats to model training, model evaluation, and model explanation. Oracle experts will walk you through a simple use case with the ADS SDK and discuss upcoming features in the roadmap.

Detect Anomalies in Your Data Using Oracle's Next Generation AI Services

Learn how to apply state-of-the-art anomaly detection technologies to identify aberrations in your time series or sensor data.

Enable Self-Service Data Discovery and Improve Data Governance

In this session, you will learn how OCI Data Catalog helps you gain insight into the data you have in Oracle Cloud and beyond. OCI Data Catalog enables data professionals—such as data analysts, data scientists, data engineers, and data stewards—to find and explore trusted data for their analyses in a truly self-service and governed manner. You’ll be shown how to harvest technical metadata, how to enrich and curate the metadata, and how to utilize these enrichments for a greatly improved search and discovery experience.

You Have a Model. Now What? Deploying Machine Learning Solutions on Autonomous Database

Data science project teams face a variety of challenges. Acquiring, exploring, and preparing data and then developing machine learning models make up a significant part of these challenges. However, the value of models is often realized only when put into production. With Oracle Machine Learning and Oracle Autonomous Database, you have a range of options for building and deploying models, whether you use in-database algorithms or open source Python algorithms. This session will explain how Oracle Autonomous Database and the Oracle Machine Learning product family can streamline model creation and deployment.

End-to-End Machine Learning Lifecycle

To meet the needs of today’s fast-paced business cycle, data scientists need to create the best models and put them into production faster and with more reliability. OCI Data Science enables data scientists to easily build, train, deploy, and manage machine learning (ML) models on Oracle Cloud using Python and open source ML libraries. Watch product experts demonstrate how to build an ML model from start to finish on OCI Data Science.

Building Intelligence: How Oracle Built a Digital Assistant

This session focuses on the real-world experience of building, training, and testing the natural language processing (NLP) models for an AI-driven digital assistant. You’ll be introduced to Artie, a digital assistant that helps Oracle developers build chatbots. Using natural language, users can ask Artie varied questions to guide their learning. To build Artie, the development team had to determine the best way to train the natural language understanding models to better understand the speaker. This session shares the good—and the bad—of building and training language intelligence in a conversational assistant.

Integrating and Preparing Data for Data Science

Data engineers and developers need to quickly prepare data for advanced analytics. From ingesting data to cleansing and integrating it from multiple data sources, OCI Data Flow and OCI Data Integration expedite and simplify the data transformation and aggregation process by eliminating the burdens of heavy coding and infrastructure operation. Learn how to radically accelerate loading and transforming data to cloud databases and data lakes for analytics or data science and AI projects. Enable your business to get data faster and make informed decisions for a more data-driven organization.

AutoML: The Future of Machine Learning?

While problem definition, data preparation, and ultimate solution evaluation are still largely human activities, new AutoML features of Oracle Machine Learning are making machine learning (ML) more accessible and effective for a wider range of users. A significant part of the ML process can be automated by addressing some of its more time-intensive and repetitive aspects. One goal for automatic ML, or AutoML, is to increase data scientist productivity while reducing the overall compute time required to derive a high quality model. At the same time, automation also enables non-experts to leverage ML, even if they do not know the finer details of the algorithms.

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

Panel: The Future of AI Development—How to Embed AI in Every Application

Join a discussion with Oracle’s AI leaders—representing Oracle Database, Oracle Fusion, NetSuite, and OCI products—to learn how they are using AI inside their applications. Hear their recommendations for how to embed AI into your own apps.

  • Moderator: Elad Ziklik

    Vice President, Product Management, AI Services and Data Science, Oracle

  • Miranda Nash

    Vice President, Product Strategy, Oracle

  • Suhas Uliyar

    Vice President, Product Management, Oracle

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

  • Ian Wilson

    Director, Engineering, IntelligentSuite, Oracle

Hands-On Lab: An Introduction to the Accelerated Data Science SDK

OCI Data Science is a fully managed and serverless platform for building, training, managing, and deploying machine learning models. It includes your favourite open-source libraries and the Accelerated Data Science (ADS) SDK. This SDK automates common data science tasks. We will build a model from scratch using ADS to do exploratory data analysis and feature engineering. We will also use AutoML to train and evaluate several models, and then use Machine Learning Explainability to understand what a black-box model is doing. Join us to learn how to use OCI Data Science to automate your data science practice.

Hands-On Lab: Using Oracle Machine Learning for Python on Autonomous Database

In this hands-on lab, 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. Sign up for this tour of OML4Py.

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

Welcome and Keynote: The Future of AI and ML—How AI Can Help Your Business

AI and machine learning are often hyped as the future of everything. So why is it such a challenge to apply AI to your specific business requirements? This keynote will consider how the world of AI services is likely to develop over the next few years and how Oracle is making it easier for AI to work for you.

  • Elad Ziklik

    Vice President, Product Management, AI Services and Data Science, Oracle

  • Manisha Gupta

    Senior Director, Product Management, Analytics Apps for HCM, Oracle

Accelerating Data Science Using the Oracle Accelerated Data Science SDK

This session provides an overview of the Oracle Accelerated Data Science (ADS) SDK, a Python library available through the OCI Data Science notebook session resource. The ADS SDK provides a series of tools and features that cover the entire lifecycle of machine learning models—from data acquired through a variety of sources and formats to model training, model evaluation, and model explanation. Oracle experts will walk you through a simple use case with the ADS SDK and discuss upcoming features in the roadmap.

Detect Anomalies in Your Data Using Oracle's Next Generation AI Services

Learn how to apply state-of-the-art anomaly detection technologies to identify aberrations in your time series or sensor data.

Enable Self-Service Data Discovery and Improve Data Governance

In this session, you will learn how OCI Data Catalog helps you gain insight into the data you have in Oracle Cloud and beyond. OCI Data Catalog enables data professionals—such as data analysts, data scientists, data engineers, and data stewards—to find and explore trusted data for their analyses in a truly self-service and governed manner. You’ll be shown how to harvest technical metadata, how to enrich and curate the metadata, and how to utilize these enrichments for a greatly improved search and discovery experience.

You Have a Model. Now What? Deploying Machine Learning Solutions on Autonomous Database

Data science project teams face a variety of challenges. Acquiring, exploring, and preparing data and then developing machine learning models make up a significant part of these challenges. However, the value of models is often realized only when put into production. With Oracle Machine Learning and Oracle Autonomous Database, you have a range of options for building and deploying models, whether you use in-database algorithms or open source Python algorithms. This session will explain how Oracle Autonomous Database and the Oracle Machine Learning product family can streamline model creation and deployment.

End-to-End Machine Learning Lifecycle

To meet the needs of today’s fast-paced business cycle, data scientists need to create the best models and put them into production faster and with more reliability. OCI Data Science enables data scientists to easily build, train, deploy, and manage machine learning (ML) models on Oracle Cloud using Python and open source ML libraries. Watch product experts demonstrate how to build an ML model from start to finish on OCI Data Science.

Building Intelligence: How Oracle Built a Digital Assistant

This session focuses on the real-world experience of building, training, and testing the natural language processing (NLP) models for an AI-driven digital assistant. You’ll be introduced to Artie, a digital assistant that helps Oracle developers build chatbots. Using natural language, users can ask Artie varied questions to guide their learning. To build Artie, the development team had to determine the best way to train the natural language understanding models to better understand the speaker. This session shares the good—and the bad—of building and training language intelligence in a conversational assistant.

Integrating and Preparing Data for Data Science

Data engineers and developers need to quickly prepare data for advanced analytics. From ingesting data to cleansing and integrating it from multiple data sources, OCI Data Flow and OCI Data Integration expedite and simplify the data transformation and aggregation process by eliminating the burdens of heavy coding and infrastructure operation. Learn how to radically accelerate loading and transforming data to cloud databases and data lakes for analytics or data science and AI projects. Enable your business to get data faster and make informed decisions for a more data-driven organization.

AutoML: The Future of Machine Learning?

While problem definition, data preparation, and ultimate solution evaluation are still largely human activities, new AutoML features of Oracle Machine Learning are making machine learning (ML) more accessible and effective for a wider range of users. A significant part of the ML process can be automated by addressing some of its more time-intensive and repetitive aspects. One goal for automatic ML, or AutoML, is to increase data scientist productivity while reducing the overall compute time required to derive a high quality model. At the same time, automation also enables non-experts to leverage ML, even if they do not know the finer details of the algorithms.

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

Panel: The Future of AI Development—How to Embed AI in Every Application

Join a discussion with Oracle’s AI leaders—representing Oracle Database, Oracle Fusion, NetSuite, and OCI products—to learn how they are using AI inside their applications. Hear their recommendations for how to embed AI into your own apps.

  • Moderator: Elad Ziklik

    Vice President, Product Management, AI Services and Data Science, Oracle

  • Miranda Nash

    Vice President, Product Strategy, Oracle

  • Suhas Uliyar

    Vice President, Product Management, Oracle

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

  • Ian Wilson

    Director, Engineering, IntelligentSuite, Oracle

Hands-On Lab: An Introduction to the Accelerated Data Science SDK

OCI Data Science is a fully managed and serverless platform for building, training, managing, and deploying machine learning models. It includes your favourite open-source libraries and the Accelerated Data Science (ADS) SDK. This SDK automates common data science tasks. We will build a model from scratch using ADS' to do an exploratory data analysis and, feature engineering. We will also, use AutoML to train and evaluate several models, and then use Machine Learning Explainability to understand what a black-box model is doing. Join us to learn how to use the Data Science service to automate your data science practice.

Hands-On Lab: Using Oracle Machine Learning for Python on Autonomous Database

In this hands-on lab, 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. Sign up for this tour of OML4Py.

  • Mark Hornick

    Senior Director, Data Science and Machine Learning Product Management, Oracle

Featured speakers

Elad Ziklik Vice President, Product Management, AI Services and Data Science, Oracle

Elad Ziklik recently joined Oracle as the vice president of product management for all Oracle Cloud Infrastructure data science and AI services. Prior to joining Oracle, Elad spent 14 years at Microsoft, working on a variety of data, machine learning, and AI products. Elad was one of the founders of Azure Cognitive Services. He’s passionate about using the magic of AI and machine learning to create innovative experiences and products.

Manisha Gupta Senior Director, Product Management, Analytics Apps for HCM, Oracle

Manisha Gupta leads the team building the HCM analytics solution used by Oracle customers worldwide. She is on a mission to analytically establish the people to profitability equation whereby performant individuals lead to productive teams which, in turn, leads to profitable companies. To do this, Manisha and her team collaborate with Oracle teams and companies across the globe. Before joining Oracle, she held global roles and built multimillion-dollar products for LinkedIn, eBay, and early-stage startups. Manisha earned an MBA from Wharton and an MS in computer science. A frequent public speaker, author, and mother, she loves traveling and enriching life with technology, psychology, and philanthropy.

Blaine Carter Senior Staff Developer, Open Source and Partner Ecosystem, Oracle

As a member of the developer relations team, Blaine Carter focuses on helping developers quickly obtain the information they need to create applications using the best technologies available. Blaine started programming in 1995. For most of his career, he has used Oracle tools to build applications, beginning with Oracle Forms and Oracle Reports. Blaine has also worked with Node.js, Java, Python, and Ruby—both inside and outside the database—and, of course, a whole bunch of SQL and PL/SQL.

Miranda Nash Vice President, Product Strategy, Oracle

Miranda Nash is vice president of product strategy for AI apps at Oracle, responsible for the AI-enabling apps in Oracle’s SaaS portfolio. She also oversees product and data operations for Oracle DataFox, an acquisition she sponsored. Previously, Miranda was an entrepreneur and leader of SaaS startups. She began her career at Oracle as an engineer, then became a product leader in data integration. Miranda holds an MBA and a BS in computer science, both from Stanford.

Suhas Uliyar Vice President, Product Management, Oracle

Suhas Uliyar is vice president of product management at Oracle, responsible for multiple Oracle Cloud services including mobile; augmented reality and virtual reality; digital assistant for conversational AI; language, speech, and document AI services; and integration and intelligent automation strategy, vision, and execution. He is a visionary, strategist, and technology evangelist responsible for designing and developing next-generation digital experiences and AI cloud services.

With more than 25 years in the mobile industry, Suhas was named one of the Top 100 Wireless Technology Experts by TodaysWireless World.com in 2014. He has a deep background in machine learning and developed the first AI-powered enterprise digital assistant in the industry. Suhas is a frequent keynote speaker at various Oracle and industry events and is often interviewed about innovative user experiences. He has technical and business management experience at both startups and enterprises in applications and platforms, digital experiences, cloud platforms, and machine learning. Suhas has held leadership positions with SAP, Motorola Solutions, Spring Wireless, Dexterra (Antenna Software), and Micromuse (IBM).

Grant Ronald Senior Director, Product Management, Oracle

Grant Ronald is a senior director of product management within the Oracle Digital Assistant development team, responsible for product strategy, evangelism, and technical enablement. At Oracle, he has global responsibility for all technical aspects of building successful digital assistants for internal and external customers. Grant leads a team of highly technical product specialists who work on one-on-one engagements with Oracle’s most critical customer implementations, and he is building a center of excellence around digital assistant best practices.

Grant is a globally recognized speaker, presenting more than 18 times at Oracle World and more than 100 times at global events across Europe, India, China, Russia, North America, and Africa. He also authored The Quick Start Guide to Fusion Developer, published by Oracle Press.

Carter Shanklin Senior Director, Product Management, Oracle

Carter Shanklin is senior director of product management for Oracle Cloud Platform, specializing in big data. Carter has more than 10 years of experience developing data management and big data products.

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

Mark Hornick is senior director of product management for Oracle Machine Learning (OML), leading the OML product management team. Mark has more than 20 years of experience integrating and leveraging machine learning with Oracle software, working with internal and external customers to apply Oracle’s machine learning technologies. He blogs at blogs.oracle.com/r and blogs.oracle.com/machinelearning. Mark is Oracle’s representative on the Board of Directors of the R Consortium, and he is an Oracle Adviser and founding member of the Analytics and Data Oracle User Community. Mark holds a bachelor’s degree from Rutgers University and a master’s degree from Brown University, both in computer science.

Jean-René Gauthier Senior Principal Product Data Scientist, Oracle

Jean-René Gauthier is a principal product data scientist and a member of the Oracle Cloud Infrastructure Data Science product team. Jean-René previously worked at DataScience.com where he designed the model management features and roadmap for the DataScience.com platform. In addition, he managed a team of data experts that developed algorithms and analytics models to solve customers’ unique business problems. He was also responsible for educating clients on these algorithms and models, ensuring that they were incorporated into the business to add maximum value. Prior to his three years at DataScience.com, Jean-René was a data scientist at AuriQ Systems where he focused on online marketing analytics and data engineering, often involving high-speed processing of massive data sets. He holds a PhD in astrophysics from the University of Chicago and was a Millikan fellow at the California Institute of Technology.

John Peach Principal Data Scientist, Oracle

John Peach is a principal data scientist working on Oracle Cloud Infrastructure (OCI) Data Science. Leveraging his extensive, hands-on experience building machine learning (ML) models, he is now defining the tooling to improve the data science workflow. A modern polymath, John possesses a unique and diverse set of skills, knowledge, and experience. With advanced degrees in engineering, kinesiology, and data science, he has built expertise in ML and finding solutions to ambiguous problems. He has a proven history of taking a product from ideation to production.

Wendy Yip Data Scientist, Oracle

Wendy Yip is a data scientist on the product management team for Oracle Cloud Infrastructure (OCI) Data Science. She joined the OCI Data Science team in November 2019. Prior to Oracle, she worked as a data scientist at companies spanning diverse industries from retail to media to enterprise software. Wendy has a PhD in electrical engineering from Northwestern University where she worked on improving optical cancer diagnostics tools.

Ranjith Narayanan Director, Software Development, Cloud AI Services, Oracle

Since joining Oracle in June 2020, Ranjith Narayanan leads software development for the anomaly detection service in Oracle Cloud Infrastructure. Prior to joining Oracle, Ranjith worked as a software architect and engineering group manager at Microsoft, heading efforts on cloud and machine learning. He also worked to enable AI on the Azure platform at large enterprises in the pharmaceuticals, energy, and manufacturing sectors.

Ian Wilson Director, Software Development, Intelligent Suite, Oracle

Ian Wilson is the director of engineering for the Intelligent Suite team at NetSuite. His team focuses on empowering the development of AI features across the NetSuite product organization. With more than 15 years of experience with building products and teams, Ian has worked in a variety of industries with a focus on data management, analytics, and AI solutions. Prior to joining Oracle, Ian led the development of Dematic InSights, a cloud solution for collecting IoT data and providing technical analysis and AI solutions for warehouse logistics.

Abhiram Gujjewar Director, Product Management, Oracle

Abhiram Gujjewar is a director of product management for Oracle Cloud Infrastructure (OCI), leading the OCI Data Catalog service. He has 20 years of experience supporting data management products in engineering and product management roles. Abhiram focuses on data integration, data quality, data governance, data catalogs, and data preparation for on premises and cloud.

Nupur Chatterji Software Developer, Oracle

Nupur joined Oracle as a software developer in March 2020 as a new graduate. She is excited to be working on interesting data science problems with the Oracle Accelerated Data Science team. Her background is in computer science, machine learning, and economics.

Ty McKercher Principal Solution Architect, NVIDIA

Ty McKercher is a principal solution architect with NVIDIA, leading a team that specializes in data science to help solve customer business problems across multiple industries. He has been engaged in the RAPIDS GPU-accelerated data analytics project since it was introduced in the fall of 2018. Ty is also a coauthor of the book CUDA C Programming, and he helps customers merge AI and high performance computing workflows using NVIDIA technologies. Ty earned his mathematics degree with emphasis in geophysics and computer science from the Colorado School of Mines.

Julien Testut Senior Principal Product Manager, Oracle

Julien Testut is a senior principal product manager for Oracle Cloud Infrastructure (OCI), focusing on data and AI services such as OCI Data Integration. He previously led product management activities for Oracle Data Integration Platform Cloud, Oracle Data Integrator (ODI), and ODI Cloud Service. Julien has an extensive background in cloud, big data, data integration, data quality, and data governance solutions. He is also a co-author of the books Getting Started with Oracle Data Integrator: A Hands-on Tutorial and Oracle Data Integrator Cookbook. Prior to joining Oracle, he was an applications engineer at Sunopsis, which was acquired by Oracle.

Elena Sunshine Senior Principal Product Manager, Oracle

Elena Sunshine is a senior principal product manager for Oracle Cloud Infrastructure (OCI) Data Science. She joined Oracle through the acquisition of DataScience.com, where she led the effort to bring the DataScience.com platform to market. Prior to her time at Oracle, she was a product leader across many verticals, solving big data and machine learning problems at large enterprises—including Verizon, AOL, and Deutsche Bank—and multiple successful startups.

Marcos Arancibia Product Manager, Data Science and Big Data, Oracle

Marcos Arancibia is the product manager for data science and big data at Oracle. He works—both on premises and in Oracle Cloud—with machine learning in the Oracle Database and on big data clusters under Hadoop and Spark. He helps develop product strategy, roadmap prioritization, product positioning, and product evangelization while working closely with the engineering team to define product roadmaps for Oracle Machine Learning and Oracle Big Data Cloud Service. Before joining Oracle nine years ago, Marcos was at SAS Institute for 13 years as a data mining architect and expert in the US and Latin America. He holds a Bachelor of Science degree in statistics, with additional master-level coursework in statistics, both from UNICAMP in Brazil. He earned on AI and machine learning from Stanford and on Computational Neuroscience from the University of Washington. He is an expert on deep learning and is passionate about machine learning.

 

Keynote preview: Elad Ziklik shares trends in #AI and #ML for enterprise #developers (2:02)

Join hands-on labs

All you need is your laptop. Oracle Cloud Free Tier accounts will be provided.

Receive your Certificate of Attendance

Attend a minimum of 90 minutes of Oracle Developer Live sessions and receive a Certificate of Attendance. Hands-on lab participation and on-demand views do not qualify.

Watch on demand

Did you miss our past Oracle Developer Live events? All sessions and self-guided hands-on labs are available on demand.

Oracle Cloud Free Tier

Build, test, and deploy applications on Oracle Cloud—for free. Sign up once, get access to two free offers.

Join virtual hands-on labs

All you need is your laptop. Oracle Cloud Free Tier accounts will be provided.

  • GPU-Accelerated Data Science with Nvidia RAPIDS
  • Time Series Forecasting with fb Prophet
  • An Introduction to the Accelerated Data Science SDK
  • Using Oracle Machine Learning for Python on Autonomous Database
Register now