A simple implementation of a perceptron on sonar dataset using Python.
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Updated
May 13, 2017 - Python
A simple implementation of a perceptron on sonar dataset using Python.
Set-Get-Do commands allow you to configure the settings on printers. This app demos how to use SGD commands to get and set the configuration variables of the printer using the Zebra Link-OS SDK.
R package implementing Gradient Descent and its variants for regression tasks
Predict the number of bikeshare users on a given day by building my own deep-learning library.
A GUI written in C++ in Ubuntu18. Draw a digit and see the recognition result. Training: k-means extracts patch features + PCA + fc layer + cost + SGD training.
MATLAB code for stochastic variance reduced multiplicative updates (SVRMU) for NMF 1.0.0
The goal is to predict how likely individuals are to receive their H1N1 and seasonal flu vaccines. Specifically, you'll be predicting two probabilities: one for h1n1_vaccine and one for seasonal_vaccine. Each row in the dataset represents one person who responded to the National 2009 H1N1 Flu Survey. For details please visit the link: https://ww…
Convert SGD images to PNG with custom palette.
Home brew Machine Learning Library implemented in Python using only the Numpy library
Logistic Regression and Optimization (Tutorial)
A simple implementation of an artificial neural network in Java. The training part uses the back propagation algorithm.
Determination the poles of Auto-Regressive Systems in Noise and poles and zeros of Auto-Regressive Moving Average system by SGD in Frequency Domain.
House Price Prediction (Kaggle)
An python implementation of Support Vector Machine from Scratch
Implementing Word2vec model using the skipgram algorithm, and train word vectors with stochastic gradient descent (SGD)
A custom example of how the stochastic gradient descent algorithm works, applied to a linear regression model.
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