Collaborative deep neural network for survival prediction of hepatitis patients using ...
->Nature | More on "Deep learning for hepatitis survival prediction" at BigEarthData.ai | #NeuralNetwork

Draw a 7. The demo shows ten probabilities and lets the little neural network make its case.

https://squoku.app/lab/
https://apps.apple.com/app/squoku/id6767931743

#MachineLearning #HandwritingRecognition #NeuralNetwork

Build a working neural network in PyTorch in just 20 minutes! Learn to train and evaluate a model to read handwritten digits with explanations right next to the code. No need for a machine learning background or a graphics card. #PyTorch #NeuralNetwork #MachineLearning

The model behind Squoku’s handwriting demo is dependency-free C++ compiled to WebAssembly. The included MNIST model reports 96.91% test accuracy.

https://squoku.app/
https://squoku.app/lab/
https://apps.apple.com/app/squoku/id6767931743

#Cpp #WebAssembly #NeuralNetwork

The handwriting lab shows its numbers: 784 grayscale inputs, 64 ReLU neurons and 10 output probabilities. It is a small proof of concept you can poke at.

https://squoku.app/
https://squoku.app/lab/
https://apps.apple.com/app/squoku/id6767931743

#NeuralNetwork #MachineLearning #WebAssembly

Draw a digit in the black square. The little neural network answers with ten probabilities, one for every digit. The demo runs in your browser.

https://squoku.app/
https://squoku.app/lab/
https://apps.apple.com/app/squoku/id6767931743

#NeuralNetwork #WebAssembly #MachineLearning

Interpretable neural network forecasting of CO₂ emissions from renewable and non ...
->Nature | More on "Neural networks forecasting CO₂ emissions" at BigEarthData.ai | #Renewable #ClimateChange #Emission #NeuralNetwork