Deep Learning Projects
Deep Transformer Soft Actor-Critic Network for Reinforcement Learning Utilize Transformer as memory module for both Actor and Policy networks Hyperparameter tuning for SAC performance Sentiment Analysis on MyAnimeList User Ratings MyAnimeList is a popular anime rating website. Predict user rating based on review using Recurrent Neural Network (RNN) Setup a data-mining pipeline utilizing self-hosted REST API with a Redis server for caching inside dockerized container Used different models (RNN with LSTM, CNN, CNN with Word2Vec embedding layers) for training and stacking model for ensemble. Achieved 94% validation accuracy with ensemble model Classification of Extended MNIST using Persistent Homology EMNIST dataset is MNIST (handwritten digit) dataset with handwritten characters Applied Persistent Homology and Principal Component Analysis to reduce the dimensionality of dataset. Reduced feature size from 784 (28x28) to 35 while retaining 99% variance Utilized libraries giotto-ai along-side standard deep learning libraries sklearn, NumPy, Tensorflow/Keras Achieved 97%-91% training-testing accuracy with a shallow neural network with only 3 hidden layers Utilization of CNN in speech recognition Classify Google Speech Command using Convolutional Neural Network (CNN) on audio data Created pipelines to process audio data to image features Audio data augmentation with respect to image features Used multiple CNN architectures (LeNet, MiniGoogleNet, AlexNet) for training and stacking model for ensemble. Achieved 91% validation accuracy with ensemble model.