Example CNN on CIFAR-10 classification

Using advanced deep learning techniques on the MNIST dataset. Over 98% validation set accuracy.

A python implementation of linear classification algorithm (including Probabilistic Generative Model, Probabilistic Discriminative Model). (See Pattern Recognition and Machine Learning, Bishop)

Tensorflow simple project using MNIST dataset and softmax-regression

This project provides a series of MxNetR example for letting readers to get started quickly.

SAGA with Perturbations

Flexible SVM framework implementation

Support vector machines flexible framework

Handwritten digit classification systems

Image Recognition on the CIFAR-10 training set using various approaches like Convolutional neural networks, Support Vector Machines, Softmax regression using only Numpy

Mixture of Softmaxes implementation in Tensorflow

Code and data for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016

Use python Jupyter notebooks (numpy, pandas, matplotlib, etc) to implement and test simple machine learning algorithms.

CS224n : Natural Language Processing with Deep Learning Assignments, Winter 2017, Stanford University.

Matlab library for gradient descent algorithms: Version 1.0.1