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1. Sports-Classifier-Deep-Learning Sports-Classifier-Deep-Learning Public

   Train a Deep Learning Model to classify images according to sport. Uses two different approaches - Basic CNN and Transfer Learning.

   Jupyter Notebook 1

2. Credit-Card-Clustering-PCA-Kmeans Credit-Card-Clustering-PCA-Kmeans Public

   Classify credit card users based on spending patterns and other metrics. Carry out PCA to reduce dimensionality and then cluster using the Kmeans algorithm.

   Jupyter Notebook 1 2

3. Predicting-College-Admissions-Random-Forest Predicting-College-Admissions-Random-Forest Public

   Use a random forest to predict the probability of being accepted into graduate programs.

   Jupyter Notebook 3

4. Neural-Network-Implementation Neural-Network-Implementation Public

   Implementation of a Neural Network written in Python. Uses the RMSProp optimizer and supports sigmoid, tanh, and ReLu activation functions.

   Python

5. Model-Selection-on-Auto-Data Model-Selection-on-Auto-Data Public

   In this R project, we use variable selection, regularization (Lasso & Ridge), PCR, and PLS to find the best model for this dataset.