keras-visualization
There are 35 repositories under keras-visualization topic.
stared/livelossplot
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
philipperemy/keract
Layers Outputs and Gradients in Keras. Made easy.
keisen/tf-keras-vis
Neural network visualization toolkit for tf.keras
alexisbcook/ResNetCAM-keras
Keras implementation of a ResNet-CAM model
joaopauloschuler/k-neural-api
K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.
alexisbcook/keras_transfer_cifar10
Object classification with CIFAR-10 using transfer learning
stared/keras-sequential-ascii
ASCII summary for simple sequential models in Keras
yashk2810/MNIST-Keras
Using various CNN techniques on the MNIST dataset
cbaziotis/keras-utilities
Utilities for Keras - Deep Learning library
mahyar-amiri/keras-visualizer
A Keras Model Visualizer
gallettilance/kviz
https://pypi.org/project/kviz/ Visualization library for keras neural networks. Contributions welcome
Hourout/beefly
Dynamic visualization training service in Jupyter Notebook for Keras tf.keras and others.
yuvalailer/nnplot
:tv: A Python library for pruning and visualizing Keras Neural Networks' structure and weights
BaseMax/ImageRecognition
Recognition of the images includes train and tests based on Python.
dhanushkamath/CIFAR-10
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.
scottherford/IDC_BreastCancer
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.
soms98/Stock-Price-Prediction-Time-Series-LSTM-Model-Keras-Tensorflow
This is a model that has been trained on historical data obtained from Yahoo Finance. The data set comprises of all data records starting from the launch date of this stock in India (1996). This model aims to pick up key trends in the stock price fluctuations based on Time Series mapping. It is able to render predictions for the upcoming time period. The accuracy as obtained on the training data-set is about 90 percent and it successfully demonstrates key trends. It can be simulated on any stock in the market provided their historical data is made available. (One could use the yfinance API or download manually). Keras is used extensively along with Tensorflow for training. The model features 100 epochs of Base size 64. The training time depends on the hardware being used by the user. It is advisable to be performed on Google Colaboratory. For any issues/suggestions write to somshankar97@gmail.com
jfilter/deep-plots
📉 Visualize your Deep Learning training in static graphics
maphdev/Deep_Visualization_Neural_Networks_Web_app
Easy way to visualize convolutional neural networks, through two visualizations : Reason & MaxOut. Final version : web app.
wikke/Kaggle-Dogs-vs-Cats
Dogs-vs-Cats image classification
ellolo/visual-keras
Visualization techiques for deep learning neural networks using Keras
DeepRoboticsResearch/AutoDL
A Deep Learning Automation Framework Library based on keras, sklearn for the automation of the machine learning and deeplearning algorithms training.testing,metrics,comparative analysis and visualisations
b-tao/X-Ray_Bone_Classifier
Convolutional Neural Network Architecture to classify Bone Fractures from X-Ray Images
nmcardoso/fitsbook-python
FitsBook Python Library. Tool for generating real-time machine learning training statistics and storing model histories. Direct integration with Keras Framework.
abidmuin/TensorFlow-in-Practice-Specialization
TensorFlow in Practice Specialization
drmerlot/Carnd-Behavioral-Cloning
Project 3 of Term 1 in the Udacity Self Driving Car Nanodegree
Feramonics/OSHA
Open Source Health Analysis
TheNudibranch/Face-Recognition
This is a repository for the code and various numpy files that going along with the face recognition project.
ArthDh/SpriteGAN
A keras implementation of DCGAN to generate Pokèmon sprites.
Gonnuru/Basketball_Prediction
In this project I have used Advanced DeepLearning techniques with keras to predict the probability of win and lose of college basketball tournaments.
jbegaint/hualos
Keras Total Visualization project
maphdev/Deep_Visualization_Neural_Networks_Terminal
Easy way to visualize convolutional neural networks, through two visualizations : Reason & MaxOut. First Version : Terminal.
nmcardoso/fitsbook
Fitsbook React WebApp. Tool for generating real-time machine learning training statistics and storing model histories. Direct integration with Keras.