DKDivyajot Kaurinai-beginners-journey.hashnode.dev·3d ago · 6 min readPart 12: Logistic Regression: How Machines Learn to Make Yes-or-No DecisionsImagine you're ordering food online. Before you place your order, the app might show you a message like: "Will your order arrive within 30 minutes?" The app doesn't know the future, but based on facto00
DKDivyajot Kaurinai-beginners-journey.hashnode.dev·Jun 20 · 4 min readPart 11: What is Gradient Descent?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 00
DKDivyajot Kaurinai-beginners-journey.hashnode.dev·Jun 11 · 4 min readPart 10: Introduction to Linear RegressionSo 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 predict00
DKDivyajot Kaurinai-beginners-journey.hashnode.dev·Jun 4 · 6 min readPart 9: Bias–Variance Tradeoff in Machine LearningImagine 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 pre00
DKDivyajot Kaurinai-beginners-journey.hashnode.dev·May 28 · 3 min readPart 8: Overfitting vs Underfitting in Machine LearningImagine 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 onl00
