My solutions to the Deep Learning course, Fall 2022, Dr. Davoodabadi
Homework 1 is about Keras basics and implementing models in both the sequential and functional API of Keras.
Homework 2 involves designing of a model for training on MNIST dataset and using different hyperparameters and optimizers and also implementing a classifier for dogs and cats.
Homework 3 includes data augmentation and prevention of overfitting in neural networks.
Homework 4 focuses on task of classification for different types of cars and using GradCAM for model interpretation.
Homework 5 is about usage of recurrent models for predicting time-series data.
Homework 6 is centered around task of self-supervised learning and also using KerasTuner for hyperparameter tuning.