Implementation of basic ML algorithms for the course ECL443

• Linear Regression
  Implementation of Linear Regression using pseudo-inverse and gradient descent methods.
• Artificial Neural Networks
  Implementation a classifier model with ANN to distinguish between cancer and normal patients.
• Support Vector Machine
  SVM classifier that can distinguish between the different types of iris.
• Convolution
  Implementation of the operations within a convolutional layer of a CNN and using them to construct a Inception module
• Principal Component Analysis and Autoencoders
  Compression of the ovarian cancer dataset using PCA(Principal Component Analysis) and Autoencoder and building a classifier that can distinguish between cancer and control/normal patients.
• Reconstruction of compressed data from PC space and from Autoencoders
  Compression of the ovarian cancer dataset using PCA(Principal Component Analysis) and Autoencoder and evaluating the effectiveness by comparing the reconstructed data with the original data.
• Datasets
  Datasets used for the assignments.