Assignments CS506
Assignment 0
- Github Link
- This is a dummy project to make sure that all is working correctly. The script will add two numbers together and print the sum to the command line.
Assignment 1
- Github Link
- This project evaluates the elevators at CDS frequency to find where the best place to stand to reduce walking is.
Assignment 2
- Github Link
- This project plots points on a 2D grid to show clustering using Kmeans with different kinds of centroid initialization. See the linked video to see the webpage using flask, and the logic in python. They are not yet integrated.
- YouTube Link
Assignment 3
- Github Link
- This project implements Singular Value Decomposition on the MNIST dataset and compares the model performance and training time when using different levels of SVD for dimensionality reduction.
Assignment 4
Assignment 5
- Github Link
- K-Nearest Neighbors Kaggle Competition to develop a predictive model to identify customers who are likely to churn (i.e., leave the bank) using the K-Nearest Neighbors (KNN) algorithm.
Midterm Kaggle Competition
- Github Link
- Create a model to predict a movie watchers review out of 5 stars based on their review’s data (text, summary, time of day, etc)
Assignment 6
Assignment 7
- Github Link
- Flask app that allows input to see the impact of changing parameters on linear regression (new to Assignment 7 includes hypothesis testing and confidence intervals through simulations)
- YouTube Link
Assignment 8
- Github Link
- Flask app that allows input to see the impact of changing parameters on linear regression (new to Assignment 7 includes hypothesis testing and confidence intervals through simulations)
- YouTube Link
Assignment 9
- Github Link
- Flask app that allows input of activation function, learning rate, and learning steps to visualize a neural network.
- YouTube Link
