These notebooks assume that you have the DeepWater version of H2O. If your don't have it, you can follow the instructions of our deepwater repository.

Note: There are many more example scripts in:

• h2o-py/tests
• h2o-py/demos
• h2o-r/tests
• h2o-r/demos

The examples assume that you run jupyter notebook from the same directory:

cd examples/deeplearning/notebooks/
jupyter notebook .

• Anomaly detection with H2O Deep Learning (CPU)
• Image reconstruction and clustering with H2O Deep Learning (CPU)

• MNIST image classification and introduction to neural networks (GPU and CPU)
• MNIST image classification with convolutional neural networks (GPU)
• CIFAR10 image classification with VGG convolutional neural network (GPU)
• Cat/Dog/Mouse image classification with Lenet convolutional neural network (GPU)
• Cat/Dog/Mouse image classification with Lenet convolutional neural network - TensorFlow (GPU)
• Cat/Dog/Mouse image classification with Inception Resnet V2 convolutional neural network (GPU)
• Credit card risk prediction with an ensemble of Deep Learning, GBM and DRF
• Iris flower classification with hyper-parameter optimization (GPU)
• Szilard's MNIST Deep Learning benchmark (GPU)

• Cat/Dog/Mouse image classification with Lenet convolutional neural network (GPU)
• Iris flower classification with hyper-parameter optimization (GPU)