keras-classification-models

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

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

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

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

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

Detecting Brest Cancer from histology images using keras.

How to use the Keras Deep Learning library

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.

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

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

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

Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI

Dogs-vs-Cats image classification

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.

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 deep learning model built to detect cataract in human eyes using the VGG-19 pretrained weights

Text Classification Lib on Keras

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

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

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

Tuning of Hyperparameters :- Batch Size and Epochs. Tuning of Hyperparameters:- Learning rate and Drop out rate. Tuning of Hyperparameters:- Activation Function and Kernel Initializer. Tuning of Hyperparameter :-Number of Neurons in activation layer. Training model with optimum values of Hyperparameters.