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Introduction to Deep Learning

Assignments and final project for the graduate course ECE 16:332:579 Introduction to Deep Learning. The file tree is listed below:

  • HW1 - Implementation of the K-nearest neighbors algorithm to classify a data point in a state space.
  • HW2 - Implementation of the back propagation algorithm without using auto grad
  • HW3 - Implementation of a neural network
    • a - Using only numpy
    • b - Using PyTorch and auto gradient
  • HW4 - Training the CIFAR10 dataset on LeNet5 CNN architecture
  • HW5 - Training and pruning a LeNet5 CNN model