bias
linear separatable binary classification problem

linear classifier, perceptron

mean squared error (mse)
metod of gradient descent
convex function
stochastic gradient descent (SGD)
least means squares (LMS) algorithm
back propagation algorithm

probability function

Bayesian decision Theory
class conditional probability
Baysean optimal classifier
Maximum Aposteriori Estimation (MAE)
Maximum Likelihood Estimation (MLE)
nearest neighbor algorithm (NN)

Naive Bayes Classifier
mutual independence assumption

supervised machine learning

probability density function
probability mass function

non-parameteic dustribution

generative AI
discriminative learning

over-fitting the data

k-NN (nearest neighbor) algorithm - non parametric model

principal component analysis or PCA
dimensionality reduction


unsupervised learning


constrained optimization problem
lageange function
method of lagrange miltipliers
decision boundary
support vectors
support vector machine

a kernel function
polynomial kernel

Hopfield networks

habian learning rules

universal approximation theorem

back propagation

coda

convolution neural network