For many, automated machine learning (or, AutoML) is a shortcut to leveraging AI in support of enterprise business objectives. AutoML automates steps in the machine learning process, and helps you leverage your domain expertise and broader data knowledge in combination with powerful machine learning algorithms.
And while there’s a lot of value to be gained, we need to keep our expectations grounded.
In this Oracle CloudWorld 2022 session, we start with automated machine learning – what it is and what can we expect from it? What business problems might we solve with AutoML? We’ll look at the benefits and how we can take advantage of AutoML. Also, how can we separate the value from the hype? And for this, we need to explore AutoML in the context of the machine learning process.
But to address getting from business problem to business solution, we need to look at automating this seemingly simple process: get some data, produce a machine learning model to extract useful patterns from that data to make predictions, and then feed those predictions to applications.
But there’s a lot more that goes into this process.
- What’s the data we’re going to use?
- How do we produce this machine learning model?
- How do we make predictions and get those predictions into applications – quickly and easily?
There’s a wide range of considerations.
Join me to learn about the ML process, the role of automation, and the tools Oracle Machine Learning provides to enable AutoML with in-database ML algorithms from both a Python API (via OML4Py) and a no-code user interface (OML AutoML UI), both through Oracle Autonomous Database. Try OML4Py and OML AutoML UI through Oracle LiveLabs workshops, such as OML Fundamentals for a closer look at these components.