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The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using transaction data from the Limit Order Book (LOB).
Deep Learning basics with Tensorflow and Keras. It includes implementing deep neural networks, feed-forward neural networks, convolutional neural networks, and a traffic sign detection system, using GTSDB and CIFAR dataset.
Designed and implemented POS taggers using Feed Forward Neural Networks and LSTMs and evaluated them using accuracy, f1 score and confusion matrix. Did extensive hyperparameter tuning to achieve high performance. INLP Assignment, Monsoon '24.
This repository introduces Artificial Intelligence with a focus on Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN). Initially intended as supplementary lecture material, it helps readers understand LSTM-RNN and its evolution since the 1990s. Modern research on LSTM-RNN uses updated notations and more concise derivations.