INFO 527 — Neural Networks: Assignment 3 (Feedforward Neural Networks). Implementation of deep, wide, and regularized feedforward neural networks using TensorFlow Keras. Includes experiments with dropout and early stopping, tested via pytest for performance verification. Part of the Master’s in MIS/ML program at the University of Arizona.

INFO 527 — Neural Networks: Assignment 1 (String-to-Vectors). Implementation of an Index class for mapping strings to numeric vectors and matrices, tested using pytest. Part of the Master’s in MIS/ML program at the University of Arizona.

INFO 527 — Neural Networks: Assignment 4. Implementation of deep learning architectures using TensorFlow Keras, including convolutional neural networks (CNNs) for image and text classification and recurrent neural networks (RNNs) for sequence modeling. Part of the Master’s in MIS/ML program at the University of Arizona.

INFO 527 — Neural Networks: Assignment 2 (Backpropagation). Implementation of a feedforward neural network with sigmoid activation and training via backpropagation using gradient descent. Includes gradient computation, prediction, and pytest validation. Part of the Master’s in MIS/ML program at the University of Arizona.

🧠 Implement convolutional and recurrent neural networks in TensorFlow Keras to handle image and text datasets, enhancing model performance through advanced techniques.