Archives
All the articles I've archived.
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Random Vectors Continued...
Exploring sums of random variables, covariance, correlation, and limit theorems (LLN & CLT). Key tools in probability and statistics to understand aggregate behavior, co-movement, and long-run patterns of random variables.
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Introduction to Random Vectors
Exploring random vectors, joint distributions, conditional distributions, and independence — the foundations of multivariate probability with real-world applications.
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Exploring Random Variable
Comprehensive exploration of probability mass, distribution, and density functions, their properties, and real-world applications.
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Hypothesis and P-Value
A quick introduction to hypothesis testing and p-values, covering their meaning, importance, and common misinterpretations in data science.
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Bayes’ Theorem — A Small Introduction
A concise, practical primer on Bayes’ Theorem: statement, formula, derivation, and real-world uses in testing, spam filtering, A/B tests, recommenders, and ML.
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Data Science Ethics
Exploring the principles, challenges, and strategies of data science ethics—covering privacy, bias, transparency, regulations, and best practices for responsible innovation.
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New Beginnings
A journey through pursuing a Master's degree in Data Science at IIT India while balancing work and personal life, exploring the transformative power of data science in today's world.