A Feature-Code Traceability Recovery Algorithm written in Python
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Updated
Aug 20, 2018 - C
A Feature-Code Traceability Recovery Algorithm written in Python
R package implementing Gradient Descent and its variants for regression tasks
My beautiful Neural Network made from scratch and love. It plays the game Flappy-Birds!
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.
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.
House Price Prediction (Kaggle)
Implementing Word2vec model using the skipgram algorithm, and train word vectors with stochastic gradient descent (SGD)
Compare performance of online-recommender system using different classification algorithm.
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