Collection of Keras models used for classification

Keras implementation of a ResNet-CAM model

Distributed Keras Engine, Make Keras faster with only one line of code.

Object classification with CIFAR-10 using transfer learning

We pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!

A simple demo / tutorial / experiment / portfolio project for me to better understand the concepts of Machine Learning

Códigos Python com diferentes aplicações como técnicas de machine learning e deep learning, fundamentos de estatística, problemas de regressão de classificação. Os vídeos com as explicações teóricas estão disponíveis no meu canal do YouTube

Implemented two papers for offline signature verification. Both use different deep learning techniques - Convolutional network and Siamese network.

Classifying 10 different categories of Sound using Deep Learning.

Classification of Time-series data with RNN

RNN classifier built with Keras to classify MNIST dataset

How to use the Keras Deep Learning library

Detecting Brest Cancer from histology images using keras.

Make a graph network of your followers. Based on username and gender

Dataset + convolutional neural network for recognizing Italian Sign Language (LIS) fingerspelling gestures

Multiclass classification example/exercise using deep neural networks (DNNs)

An IPython notebook demonstrating the process of Transfer Learning using pre-trained Convolutional Neural Networks with Keras on the popular CIFAR-10 Image Classification dataset.

Breast cancer is the most common form of cancer in women, and invasive ductal carcinoma (IDC) is the most common form of breast cancer. Accurately identifying and categorizing breast cancer subtypes is an important clinical task, and automated methods can be used to save time and reduce error. The goal of this script is to identify IDC when it is present in otherwise unlabeled histopathology images. The dataset consists of approximately five thousand 50x50 pixel RGB digital images of H&E-stained breast histopathology samples that are labeled as either IDC or non-IDC. These numpy arrays are small patches that were extracted from digital images of breast tissue samples. The breast tissue contains many cells but only some of them are cancerous. Patches that are labeled "1" contain cells that are characteristic of invasive ductal carcinoma. For more information about the data, see https://www.ncbi.nlm.nih.gov/pubmed/27563488 and http://spie.org/Publications/Proceedings/Paper/10.1117/12.2043872.

Android malware classification using both .java files and .so files

Dogs-vs-Cats image classification

Image Classification using TensorFlow Mobile, Slim and Keras

UCI Thyroid Classification - Python, Keras, scikit-learn, ANN

Deep Learning Model for classifying Monuments in Goa Using Keras

A convolution neural network based framework to classify images(of objects) into corresponding categories

Image Recognition using Deep Convolutional Network and Training Pre-trained Models ("Inception")

This project applies Natural Language Procesing with Deep Learning to classify Spam SMS

Keras implementation for Binary classification problem (Detects Pneumonia by taking X-Ray images of patient chest).

Android App that detects human face and recognize his/her expressions in real-time.

Image classification using keras with tensorflow as backend

skin-lesion-classifier