Rutgers University Python Cluster Training Dataset Project Use Python as programming language. You will be provided a training dataset (60k) and a test dataset (10k) of handwritten digits. (http://yann.lecun.com/exdb/mnist/)
Question #1:
-Cluster training dataset with K=10 and assign a class to each cluster based on majority vote
-Compute the training accuracy. Use each clusterÂ’s centroid as the anchor point and obtain the centroids
-Assign image to nearest centroid and test accuracy
Question #2:
-Build 2 non DNN based classifiers using all pixels as features for handwriting recognition. Use 2 of these techniques: Logistic regression, SVM, Decision tree, Random forest
-For each technique: describe technique, pros/cons, results
Question #3:
-You will be given a dataset of neural network and a python file for partial code
-Implement CNN (Convolutional Neural Network). Finish the Python code and report accuracy
Question #4:
-Hand write 5 styles of digits 0 to 9 on paper. Take a picture of each (50 total).
-Convert images to MNIST format
-Run ML models from question 1-3 and report accuracy
-Accuracy results of the 50 images should be shown in a table for each of the models
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