Repository for Assignment 1 for CS 725
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Updated
Sep 17, 2017 - Python
Repository for Assignment 1 for CS 725
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An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.
A framework for implementing convolutional neural networks and fully connected neural network.
Fully connected neural network with Adam optimizer, L2 regularization, Batch normalization, and Dropout using only numpy
Implementation of linear regression with L2 regularization (ridge regression) using numpy.
This repository contains the second, of 2, homework of the Machine Learning course taught by Prof. Luca Iocchi.
Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.
Mathematical machine learning algorithm implementations
Multivariate Linear and Logistic Regression Using Gradient Descent Optimization.
Multivariate Regression and Classification Using a Feed-Forward Neural Network and Gradient Descent Optimization.
PyTorch implementation of important functions for WAIL and GMMIL
Regularized Logistic Regression
Implementation of optimization and regularization algorithms in deep neural networks from scratch
This repository contains the code for the blog post on Understanding L1 and L2 regularization in machine learning. For further details, please refer to this post.
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