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A repository for NextGen Fellows 2020 at Carnegie Mellon University with Elizabeth A. Holm

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NextGen Fellows 2021 Repository

Last update: June 7, 2021

This repository serves the 2021 NextGen Fellows at Carnegie Mellon University under Prof. Elizabeth Holm.

We'll push new notebooks to this repository prior to our discussions (kind of like a Canvas page). Feel free to clone this repository and pull when we send word of updates.

Seminars for the first week are scheduled where we'll cover some basic concepts to bring you up to speed with some ideas and methods that we'll explore in this program.

Day Topic Resources Instructor
Monday, June 7, 2021 Introduction:
NextGen Program
CV/ML for microstructure
Overview paper
Set of group papers
Liz
Tuesday, June 8, 2021 Data featurizing and dimensionality reduction by PCA Class notes Srujana
Wednesday, June 9, 2021 Image representation using CNNs Slides
Web resources
Bo
Thursday, June 10, 2021 Clustering by k-Means and t-SNE Class notes Ryan
Friday, June 11, 2021 Supervised machine learning with SVM Class notes Katelyn

We will also go over some hands-on tutorials to help you practice new skills. These are just a start; we're excited to see where you take your research project!

Day Topic Goals Instructor
Monday, June 7, 2021 Set up Jupyter notebooks:
Acquire steel defects data and create Pandas dataframe
-Display images by class
-Data structured for subsequent analyses
Andrew
Tuesday, June 8, 2021 Traditional image representation:
Represent images as brightness histograms
-Compute and store brightness histograms for all images
-Compute average brightness histogram for each class and show they are different
Nan
Wednesday, June 9, 2021 CNN image representation:
Represent images using CNN layers
-Compute and store representations of all images based on two layers of pre-trained VGG16: FC1 and shallow layers
-Visualize feature vectors
Bo
Thursday, June 10, 2021 Unsupervised learning:
Cluster each representation using k-means and t-SNE
-k-means and t-SNE plots for each representation, color coded by ground truth
-Compare representations and clustering methods
Ryan
Friday, June 11, 2021 Supervised learning: SVM
Train and evaluate SVM
-Classification performance (confusion matrices) for each representation Katelyn

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