Talks

Kaggle Grandmaster Panel at H2O World India 2023
AI for Good: H2O Olympics Hackathon – Winner Announcement at H2O World India 2023

Machine Learning explainability refers to understanding and interpreting the decisions and predictions made by a machine learning model. Explainability is crucial for ensuring the trustworthiness and transparency of machine learning models, particularly in high-stakes situations where the consequences of incorrect predictions can be significant.

Parul Pandey – Kaggle Grandmaster & ML for High Risk Applications #30

Fireside chat at Amazon

Digital Transformation with AI

WIDS Hyderabad 2021 Conference

Growth of Automated ML in Industry

Career Transitioning into Data Science

Women in Data Science, Hyderabad workshop

Lightening Talk at Mindhack Summit

PyConf Hyderabad 2020 – 6th Dec,2020

Python and Data Science: A winning Combination.

Webinar for Andhra Pradesh State Skill Development Corporation(APSSDC) -21st Nov,2020
Creating a Career in Data Science with WiCDS

Data Science Conference Europe 2020 – 19th Nov,2020

How to start the Data Science journey

ICFAI Business School(IBS) Hyderabad Talk – 13th Nov,2020

Predictive Analytics – An industry perspective

Machine Learning for Everyone(ML4E), National Institute of Technology, Rourkela -3rd Oct,2020

Kaggler’s Talk- EP01: How to use Kaggle to create a Data Science portfolio?

Kaggle Days Hyderabad Meetup