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Part 11: What is Gradient Descent?

18h ago · 4 min read · In the previous blog, we learned how Linear Regression finds a best-fit line to make predictions. But an important question remains: How does the model know which line is the best? The answer lies in

Part 10: Introduction to Linear Regression

Jun 11 · 4 min read · So far in this series, we've explored datasets, preprocessing, train-test splitting, overfitting, underfitting, bias, and variance. Now it's time to dive into the algorithms that actually make predict

Part 9: Bias–Variance Tradeoff in Machine Learning

Jun 4 · 6 min read · Imagine two students preparing for an exam. One student studies only a few topics and performs poorly because they don't understand enough concepts. Another student memorizes every question from pre

Part 8: Overfitting vs Underfitting in Machine Learning

May 28 · 3 min read · Imagine a student preparing for an exam. One student memorizes every single question and answer from previous papers without actually understanding the concepts. Another student barely studies and onl

Part 7: Why We Split Data in Machine Learning?

May 27 · 5 min read · Imagine preparing for an important exam. You don’t just: Read the textbook Memorize every question And walk into the final exam directly Instead, you usually: Study concepts Practice with mock