Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
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Updated
Dec 9, 2018 - Python
Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
Machine learning library for classification tasks
Recognize users of mobile devices from accelerometer data ( Accelerometer Biometric Competition on kaggle)
The code for Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA)
Diabetes detection in patients using different machine learning techniques and comparing the algorithms based on confusion matrix and other metrics.
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Machine Learning Project
A Python library of 'old school' machine learning methods such as linear regression, logistic regression, naive Bayes, k-nearest neighbors, decision trees, and support vector machines.
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