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DataHour: Introduction to Federated Learning

Online 22-10-2022 03:00 PM to 22-10-2022 04:00 PM
  • 4974

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  • Knowledge and Learning

    Prizes

DataHour Recording

Find the resources used in the DataHour HERE.

About the DataHour:

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.


Who is this DataHour for?

  • Students & Freshers who want to build a career in the Data-tech domain.
  • Working professionals who want to transition to the Data-tech domain.
  • Data science professionals who want to accelerate their career growth


Speaker:

Tejas Pancholi

TPM - Data Science at Aera Technology

Tejas is currently working with Aera Technology as a TPM in Data science where he brings cross functional and cross culture teams to work on highly challenging cutting edge solutions to be delivered on time every day. He has an experience of  15+ years in innovating and industrializing new offerings and solutions in the data science and analytics space as he has worked on 10+ SaaS AI solutions ranging from Data Engineering to ML Models to ML Ops to Dashboard and Reporting in the domain of healthcare, Retail, Advertising/Marketing/Sales, E Commerce, supply chain, Banking and Telecommunication. He has helped end users make go-no-go decisions, create optimized loyalty plans, healthcare plans and service offering packages, run simulations on different scenarios to optimize market spend, identify target customer segments and create complex user specific ad, product offering, and shopping experience. 

He has also led 10+ senior cross geo-located teams of engineers and researchers and is recognised for his value-based customer focused leadership style, collaborative approach and ability to convert complex technical requirements into tangible action plans.

Connect with Tejas Pancholi on linkedin

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