Lab assignments from class ECE-5307, Fall 2022, OSU
This repository contains 10 folders, consisting of 9 weekly lab assignments and1 final project. Each lab assignment folder (lab 1 - lab 9) contains the input data (if any) and code (.ipynb file).
Topic of discussion in each folder is given as follows:
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Lab 1: Simple Linear Regression on Boston Housing Data
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Lab 2: Multiple Linear Regression for Robot Calibration
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Lab 3: Polynomial Regression and model order selection for Ames Iowa housing data
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Lab 4: Perform LASSA and Ridge regression, select regularization level via cross-validation on a real EEG dataset
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Lab 5: Multi-class Logistic Regression for gene expression data, confusion matrix, and L1 regularization
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Lab 6: Nonlinear Least-Squares for Modeling Materials, implement gradient descent and momentum gradient descent, and visualize convergence
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Lab 7: Digit recognition on EMNIST dataset using SVM with GridSearchCV method
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Lab 8: Neural Networks for Music Classification using PyTorch package
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Lab 9: Transfer Learning with a Pre-Trained Deep Neural Network by building a custom image dataset and fine tuning the final layers of an existing deep neural network for a new classification task
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Project: Binary classification using Linear Methods, Neural Networks Methods, and Tree-based Methods