DataHour: A Simple Guide to Deep Metric Learning

Online 12-03-2023 03:00 PM to 12-03-2023 04:00 PM
  • 4370


  • Knowledge and Learning.


About the DataHour:

Deep metric learning is a technique that focuses on determining the similarity or dissimilarity between data through the use of a distance metric. One approach to deep metric learning is the use of Siamese networks. When training a Siamese network for deep metric learning, two common loss functions are used: Contrastive Loss and Triplet Loss. 

In this DataHour session, we will learn about training a Siamese network using the Triplets loss function, with the sample image dataset. Which can be further used to build a visual search engine, object reidentifications, and face verification tasks.  

The zeal for learning new technologies, and good to have a conceptual understanding of how neural network works. 

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


Udaya A S

Data Scientist at Jio

Udaya is a highly skilled data scientist at Jio, with a strong track record of delivering high-quality, data-driven solutions that meet business needs. With five years of experience in the field, Udaya specializes in developing recommendation engines and computer vision models for production-level applications. He has deep expertise in data pre-processing, feature engineering, modelling, and deployment, which has allowed him to successfully deliver complex projects across a range of industries. Udaya's ability to develop innovative solutions, combined with his attention to detail and analytical skills, make him a valuable asset to any team.

Connect with him on Linkedin


Please register/login to participate in the contest

Please register to participate in the contest

Please register to participate in the contest



We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy.


We believe in making Analytics Vidhya the best experience possible for Data Science enthusiasts. Help us by providing valuable Feedback.