DataHour: Introduction to GAN - A Practical Approach

Online 30-08-2022 08:30 PM to 30-08-2022 09:30 PM
  • 9763


  • Knowledge and Learning


DataHour Recording

About the DataHour:

GAN - Generative Adversarial Network is a deep learning method similar to Convolution neural network.  It is an unsupervised learning task which helps in automatically finding and learning the regularities or patterns which easily is not recognizable from the test data set used and create new data from it.  

GANs are rapidly dominating and changing how we used to create models for image classification.  Few of the areas where its most impactful have been fake people identification, photorealistic photo generation which are hard for a human to distinguish.

In this DataHour, we would be learning about CNN and how GAN can improve the performance of the same.  We would look at a few practical examples using open source data sets available.  At the end we would look at fast ai library which is a very important topic that everyone should be aware about and how it can help in the practical aspect of deep learning.

Prerequisites:  Enthusiasm for learning Data Science and a laptop with good internet connection.


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



Hiral Raval

Product Manager at University Living

Currently, Hiral is Product Manager at University Living. She loves to solve business problems with data-driven insights. She has experience in collaborating with client engineering teams, creating business product specifications, prioritizing and building roadmaps, understanding the data nuances, and enabling the pipelines to report by building KPIs for Business Intelligence and AI/ Machine Learning models.

She is a strong supporter of women in Tech and loves Data science, AI/ML and she’s an active contributor to the local community. 

You can follow her on Linkedin.


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