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A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.
Single layer Neural Network
fast iterative support vector machine algorithm for linearly separable dataset. Makes use of elementary geometry; no quadratic programming,
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
displaying perceptron algorithm to its core