Implementation of Machine Learning algorithms using Python3.
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Updated
Dec 1, 2020 - Python
Implementation of Machine Learning algorithms using Python3.
Comparison of common loss functions in PyTorch using MNIST dataset
A framework to compute threshold sensitivity of deep networks to visual stimuli.
Linear classifier using logistic regression with only 2 features for MNIST Database.
MNIST digit classification with a Neural Network.
Implementation of KDTree from scratch and implement kdtree classifier and linear classifier on two different datasets.
A simple Flask application for data preprocessing, visualization and classification
Multi-class classifier with only 2 features for MNIST Database.
Natural Language Processing (COMP 550) Project
Generating decision making algorithms by evolutionary / genetic algorithm
A Python library to implement the perceptron algorithm and possibly visualize it.
A SVM classifier coded in Python using Scikit-Learn to classify whether a patient's tumor is malignant or benign.
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