based on paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim

Keras implementation of VGG from the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition" - https://arxiv.org/abs/1409.1556

various deep learning models in python

Implemented various deep learning problems of supervised learning using keras with tensorflow as backend .

Find the origin of words in every language using a Deep Neural Network trained to create an etymological map.

This is a repository for the code and various numpy files that going along with the face recognition project.

Examples of using Keras word embedding to perform sentiment analysis on IMDB and Reuters datasets.

Exploring keras and NN with Binary classification problem

Permutation learning Sinkhorn layer implementation in keras

Single Shot MultiBox Detector

An implementation of Neural Style Transfer in Keras

A recurrent neural network implementation with attention to convert human readable dates ("20th April 2000") to machine readable dates ("2000-04-20")

A tensorflow.js Rock-Paper-Scissors Model running on a Flask server

A deep neural network with tensorflow and keras using mnist dataset

Exploring the discriminating power of different loss functions for classification

Examples and tutorials to the steppy library

Analysing graph by Siamese-Network

Modeling deep learning methodologies

Attention mechanism Implementation for Keras.

In this project, my code will accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling.