- Course
- AI
AIOps: Federated Learning
We often need to use data from proprietary sources to fine tune GenAI models, and individual sources of this data should not know about data from the other sources. This course will teach you how to perform federated learning, which allows the use of data from various sources without those sources knowing about one another.
What you'll learn
In today’s world, we need to use data from diverse sources, and this data is often proprietary. Therefore, each individual data source should not know about data coming from the other sources. In this course, AIOps: Federated Learning, you’ll learn to use federated learning to combine data from various sources, without those sources knowing about one-another. First, you’ll explore the concept of federated learning. Next, you’ll discover how to use Flower for federated learning. Finally, you’ll learn how to implement a federated learning example. When you’re finished with this course, you’ll have the skills and knowledge of federated learning needed to fine tune a GenAI model using proprietary data from disparate sources.
Table of contents
About the author
David loves learning!! Indeed, his hobby is reading technical documentation. He also loves helping others learn!! Dave comes to Pluralsight with a wealth of knowledge in computer science, big data, generative AI, math, statistics, video production, and, if anyone is interested, he also can help people know how to farm pigs. He will learn about anything that interests him and will teach whoever will listen. He makes his home in the desert of southwest Utah because he doesn't like snow. He also likes Vegas, which is only 1.5 hours away, so that helps, too.