A Mechanical Engineer, with acquired skills(in Python, Machine Learning & Data Science), an insatiable intellectual curiosity, and the ability to leverage a heavy dose of Mathematics and Applied Statistics with visualization and a healthy sense of exploration. Passionate about Machine Learning with a problem-solving attitude and keen to develop deeper expertise and gain exposure in the ML, DL and NLP space.
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Aug 24, 2023 路 3 min read 路 In the ever-evolving landscape of machine learning, the journey from theory to implementation can often be daunting. Enter Conformal Prediction (CP), a powerful framework that doesn't just quantify prediction uncertainty, but equips data scientists w...
Join discussionAug 24, 2023 路 3 min read 路 In the vast landscape of machine learning, predictive models often shine brightly with their ability to forecast outcomes. However, lurking beneath their accurate predictions lies a shadow of uncertainty. Enter Conformal Prediction (CP), a potent fra...
Join discussionAug 24, 2023 路 4 min read 路 In the quest to unravel causal relationships from observational data, data scientists wield a diverse arsenal of tools. Among these, two powerful methodologies stand out: Generalized Difference-in-Differences (GDD) and Synthetic Control. These method...
Join discussionAug 15, 2023 路 3 min read 路 In the realm of causal inference, Difference-in-Differences (DiD) analysis stands tall as a robust tool for understanding the effects of interventions, policies, or treatments. This method allows data scientists to unravel causal relationships within...
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Aug 15, 2023 路 4 min read 路 Logistic regression is a vital technique in the realm of data analysis and predictive modeling, especially when dealing with binary outcomes. In this article, we will delve into the mathematical underpinnings of logistic regression, explore its key a...
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