A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.

Any linearly separable data can be given as input and it will predict the outcome of a new input based on the past inputs by giving them the appropriate weights to the synapses [SLP]

Here I create a file that using perceptron to classify linearly separable dataset on 2d and 3d space

Single layer Neural Network

fast iterative support vector machine algorithm for linearly separable dataset. Makes use of elementary geometry; no quadratic programming,

displaying perceptron algorithm to its core