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CSE_472_Machine_Learning

This repository contains the assignments of the course CSE 472 Machine Learning. The assignments are implemented in Python. The assignments are as follows:

Assignment 1: Matrix Transformation and Eigen Decomposition

See the details here

Assignment 2: Logistic Regression and AdaBoost for Classification

See the details here

Here we used 3 datasets for classification. The datasets are:

  1. Telco Customer Churn Dataset
  2. Adult Dataset
  3. Credit Card Fraud Dataset

First, we preprocessed the datasets. Then we applied Logistic Regression and AdaBoost for classification. We compared the performance of the models using different metrics.

See the results here

Assignment 3: Feed Forward Neural Network from Scratch

See the details here

Here we implemented a Feed Forward Neural Network from scratch. We used the MNIST dataset for training and testing the model. We used ReLU as the activation function and Cross Entropy Loss as the loss function. We used Mini Batch Gradient Descent for optimization.

See the results here

Assignment 4: PCA and EM Algorithm

See the details here

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CSE 472 Machine Learning Sessional

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