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DataHour: How to tackle Overfitting?

Online 17-09-2022 03:00 PM to 17-09-2022 04:00 PM
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DataHour Recording

Find the resources used in the DataHour HERE.

About the DataHour:

Overfitting is a serious issue in the machine learning  world where a model fits very well in the training data but the performance deteriorates in the test data. The session will cater around different methods to tackle overfitting. 

In this DataHour, the speaker will cover how to reduce overfitting from the data preparation stage (like CSI), what are the different things to look after while selecting cohorts. Then what are the different tips and tricks that can be followed to tackle overfitting in the model building stage like use of regularization, covariate shift analysis ,model ensembling  etc.

Prerequisites:  Enthusiasm to learn Data Science and some preliminary ideas on Machine and Deep Learning along with the basic knowledge on Python and Pythonic platforms like Keras, TensorFlow, PyTorch, Mxnet would be beneficial. 


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:

Subhodeep Mukherjee

Data Scientist II at Amazon

Subhodeep is a data science professional with 7+ years work experience currently working in Amazon as Data Scientist II. Prior to Amazon he has worked in Citi, ITC Infotech and Rainman Consulting. He has cross domain experience with experience in FMCG/CPG , Retail, HR, BFSI , Reliability spaces.  Academic wise, he has done Masters in Statistics from Calcutta University, Kolkata. 

You can follow him on Linkedin

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