Machine Learning Bias

amrrs


Description:

We have been constantly told this statement “Computers don’t lie”. Yes in fact Computers don’t lie, but neither does it speak the truth. A computer does what its Master programs it to do. Similarly, A model wouldn’t lie unless the Machine Learning Engineer doesn’t want it to lie. ML Bias has become a global topic with AI getting into social life of a lot of us but the awareness among the tech community is still nascent that not all of us get it. This is an attempt to increase the awareness of what's ML Bias and how it's impacting!

Outline:

  • Recognizing the problem (with samples of Machine Learning Bias) - 5 mins
  • What's Machine Learning Bias (attempting to formulating a definition) - 5 mins
  • Definition of Fairness (understanding fairness and potential causes of bias) - 10 mins
  • Interpretable Machine Learning - 5 mins
  • Case Study (If time permits) - 5 mins

Prerequisites:

  • Basic understanding of Data Science and its applications
  • Knowledge of Data Science Workflow

Speaker Info:

Abdul Majed is an Analytics Consultant helping Organizations make sense some out of the massive - often not knowing what to do - data. Always amazed by Open Source and its contributors and trying to be one of them.

Organizer @ Bengaluru R user Group (BRUG) Organizer

Contributed to Open source by publishing packages on CRAN and PyPi

Writer @ Towards Data Science and DataScience+

Speaker Links:

https://datascienceplus.com/author/abdulmajed-raja/

Id: 1278
Section: Data Science, Machine Learning and AI
Type: Talks
Target Audience: Intermediate
Last Updated: