DataHour: Introduction to Federated Learning
DataHour: Introduction to Federated Learning
22 Oct 202209:10am - 22 Oct 202210:10am
DataHour: Introduction to Federated Learning
About the Event
Federated learning is a new concept in machine learning which brings a decentralization concept to the AI field. It allows the model to be trained on the multiple-edge device instead of one central location being used for training. Basically we are bringing the model to the data source rather than bringing data to the model. The major advantage of this decentralized concept is data security and privacy. Areas such as defense and healthcare are deemed to get the most benefit due to this concept. Some of the most used applications of federated learning in our day-to-day life are google keyboard on our android device, the Netflix recommendation engine.
In this DataHour, Tejas will teach the basic concept of federated learning, the algorithm/library that supports the development in this area, and go over a simple example of a model created using this technique. This session can be used as a launchpad for aspirants to learn the basics and then become more proficient in the area.
Prerequisites:Understanding of Basic Python and ML concepts and curiosity of learning Data Science.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker
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