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visualizedata-ml's Introduction

Machine Learning / Parsons School of Design / Spring 2020

Assignment 1:

Process Documentation located in: This Folder

Summary:

Explore toxic comment data from Wikipedia, and learn a model to produce the highest prediction of toxicity for a new unknown dataset after training. Explored Ordinary Least Squares (OLS), Support Vector Machine, Logistic Regression, Naive Bayes, Perceptron, Ridge Regression Classifier, and Random Forest Classifier.

  • Final Submission Here

Assignment 2:

Process Documentation located in: This Folder

Summary:

Classify images of airplanes in over 6700 images. Explore a number of image processing algorithms and filters using scikit-image. Look at Sobel filters, Histogram of Oriented Gradients, etc.

  • Final Submission Here

Assignment 3:

Process Documentation located in: This Folder

Summary;

Using Unsupervised learning and specifically K-Means, cluster ~ 400 images of artwork from museum collections and galleries across several countries, curated and analyzed for inspiration and information on effective ways to visually communicate uncertainty, ambiguity, and vulnerability. The selected artworks were chosen for their unique ability to convey uncertainty using a range of approaches and techniques.

  • Final Submission Here

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