Kaggle - Digit Recognizer - CNN 99.4% Accuracy

Imaged below is the basic Convolutional Neural Network (CNN) for the Kaggle - Digit Recognizer competition.

Digit Recognizer - Convolutional Neural Network

Below provides an overview ensembling the CNN model. With executing the fit_model function 5 times, a total of a 125 epochs were executed.

Running predictions against the test set for each model and averaging the prediction for each image.

After exporting and submitting results, the basic CNN achieved 99.4% accuracy.

Kaggle - Invasive Species Monitoring - Ensemble with ROC of 0.95532

Ensemble (Bucket of models) multiple models to achieve ROC of 0.95532.

Below is an example of creating 4 models that were trained for 100 epochs each. The last section of code saves the weights for each model in the set. 

Each model was then used to predict the test image set. The mean prediction for each image was then used for the Kaggle Invasive Species Monitoring competition submission.