Gradient Descent Simplified: How Machines Learn from DataIn this blog, we’ll break down the core concepts of Gradient Descent, from optimizing models to reducing errors, making it easier for…Feb 12Feb 12
Balancing Metrics for Informed Decisions in Hypothesis Testing“Without data, you’re just another person with an opinion.” — W. Edwards DemingSep 28, 2024Sep 28, 2024
Data Science and Probability: Breaking Down the BasicsWhen diving into data science, probability is one of the first concepts you will encounter. Understanding it is crucial because, at its…Aug 25, 2024Aug 25, 2024
Covariance, Correlation, and Causation: When Two Variables Dance, Who’s Leading the Show?So, you have crunched some numbers, plotted your data, and now staring at the tangled web of relationships between variables, trying to…Aug 17, 2024Aug 17, 2024
Crunching Numbers: From Averages to Outliers and Everything In BetweenEver wondered how we turn raw data into actionable insights? It’s not magic — it’s statistics! In this blog, we’ll roll up our sleeves and…Aug 10, 2024Aug 10, 2024
From Brain Injury Biomechanics to Data Science: A Journey of Curiosity and Crunching NumbersImagine this — I was deeply immersed in brain injury research, running countless simulations and working with tons of data to understand…Aug 3, 2024Aug 3, 2024
