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ML-from-scratch

ML and DL Alogorithms

Contains from scratch:

-> Logistic Regression

-> Support Vector Machine

-> A sigmoid neuron trained on both self generated and a dataset.

-> Multiple classes of Feed Forward Neural Networks.

-> A vectorized backprop utilising FFNN.

-> A vectorized FFNN working with algorithms like vanilla Gradient Descent, Momentum Based Gradient Descent, Nesterov Accelerated Gradient Descent, AdaGrad, RMSProp and Adam.

-> A FFNN built using PyTorch functions slowly increasing the abstraction with multiple classes.

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Basic ML Alogorithms from scratch

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