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Model search in traditional machine learning algorithms (non DL) and DL starter codes on MNIST dataset. This is a good starter code for beginners trying to learn about curse of dimensionality, overfitting and other concepts in general
I had created this in the year 2012, when I was doing my 10th standard schooling. This program uses difference equation concept to predict the next value in a polynomial series.
A study of the problem of overfitting in deep neural networks, how it can be detected, and prevented using the EMNIST dataset. This was done by performing experiments with depth and width, dropout, L1 & L2 regularization, and Maxout networks.
In this repository you will learn how to handle overfitting with the help of Lasso and Ridge Regression regularizations, also working mechanism of those while using useful charts.