Classical ML and Deep Learning
Generalized Linear Models (GLMs): The Supercharged Linear Regression
The limitations of linear regression and how GLMs solve them.
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Classical ML and Deep Learning
Why Sklearn’s Logistic Regression Has no Learning Rate Hyperparameter?
What are we missing here?
Classical ML and Deep Learning
Why Do We Use log-loss To Train Logistic Regression?
The origin of log-loss.
Classical ML and Deep Learning
Why Do We Use Sigmoid in Logistic Regression?
The origin of the Sigmoid function and a guide on modeling classification datasets.
Classical ML and Deep Learning
The Probabilistic Origin of Regularization
Where did the regularization term come from?
Classical ML and Deep Learning
Where Did The Assumptions of Linear Regression Originate From?
The most extensive and in-depth guide to linear regression.
Classical ML and Deep Learning
Why is ReLU a Non-Linear Activation Function?
The most intuitive guide to ReLU activation function ever.
