Some of the tasks for Advanced Machine Learning Technologies Course at ITMO University.

1. Interpretable ML
2. Image Quality Assessment

The task is to analyze the feature importance in the dataset for making predictions by the trained model LIME frameworks. The datast is a set of labeled messages, a Naive Bayes model was trained to classify messages to: 'spam' or 'ham'. Then LIME was used to explain the prediction of the model over one test example.

The file contains different non reference image quality assessments applied on a dataset of 20 images. The results are compared to my own ranking of the images by computing pearson correlation.