In single-variable calculus, the derivative tells us how a function changes at a point - how steep the hill is under your feet. But as we step into higher dimensions, the concept evolves dramatically. Suddenly, we're not just talking about slopes, but about gradients that point...
When is a function said continuous? What conditions must a function satisfy to be considered continuous?
A formal definition of functions. And when do we call a function linear, affine, or quadratic?
A coordinate system is "a way to define locations in space", typically using numbers or coordinates. It's an arrangement of lines or curves that define the position of points or other geometric elements in space. The most commonly used coordinate systems are the Cartesian system and...
Can a simple neural network really model any Boolean function? While a single-layer perceptron struggles with non-linearly separable problems like XOR, a multi-layer perceptron (MLP) breaks through these limitations - making it a universal Boolean function approximator!
Ever wondered how we find the best possible parameters for a model? MLE - the gold standard for parameter estimation.
A linear regression model may overfit the training data. How can we reduce overfitting and improve generalization performance?
How do we find the best-fit line through a cloud of data points? The Least Squares Method holds the key! By minimizing errors, this simple yet powerful technique makes Linear Regression the go-to tool for predictions.
Why is the defeat of a Go champion by an AI from DeepMind considered a breakthrough in artificial intelligence, while chess is not seen in the same light?
Can a simple algorithm mimic how we think and make decisions? Enter the Perceptron - a groundbreaking idea that transformed AI. But how does this single-layer model draw the line between decisions?
Endeavor bachelor but add eat pleasure doubtful sociable. Age forming covered you entered the examine. Blessing scarcely confined her contempt wondered shy.