miniprojects-deep-learning

Polynomial regression

We explore the effects of increasing the training dataset size, adjusting model complexity, introducing noise to the data, and employing weight decay regularization during training.

Classification of Handwritten Digits (MNIST Dataset)

Classification using Softmax, Multilayer Perceptron (MLP) and Convolutional Neural Network (CNN) classifiers, comparing accuracy and loss performance in their training and testing phases.

Sentiment Analysis (IMDB Movie Review Dataset)

Classification using Vanilla-RNN and LSTM.

Image Generation of Handwritten Digits (MNIST Dataset)

Using Variational AutoEncoder (VAE) and Generative Adversarial Network (GAN).

Image Generation (CIFAR10 Dataset)

Using Variational AutoEncoder (VAE) and Generative Adversarial Network (GAN).