Building Convolutional Neural Networks From Scratch using NumPy

Represent trained machine learning models as Pyomo optimization formulations

Implementation of Dynamic ReLU on Pytorch

An image recognition/object detection model that detects handwritten digits and simple math operators. The output of the predicted objects (numbers & math operators) is then evaluated and solved.

Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.

Implementation of key concepts of neuralnetwork via numpy

Numpy implementation of deep learning

QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch

Deep Learning

Compare vanishing gradient problem case by case.

An algorithm that facilitates communication between a speech-impaired person and someone who doesn't understand sign language using convolution neural networks

Simple multi layer perceptron application using feed forward back propagation algorithm

Avoiding the vanishing gradients problem by adding random noise and batch normalization

TorchAct, collection of activation function for PyTorch. https://pypi.org/project/torchact/

Experiments using different activation functions.

An algorithm that facilitates communication between a speech-impaired person and someone who doesn't understand sign language using neural networks

Neural Network from scratch without any machine learning libraries

GAAF implementation on Keras

Investigating the Behaviour of Deep Neural Networks for Classification