Usage

Train a new network on a data set with train.py

• Basic usage: python train.py data_directory

Prints out training loss, validation loss, and validation accuracy as the network trains

Options:

• Set directory to save checkpoints: python train.py data_dir --save_dir save_directory

• Choose architecture: python train.py data_dir --arch "vgg13"

• Set hyperparameters: python train.py data_dir --learning_rate 0.01 --hidden_units 512 --epochs 20

• Use GPU for training: python train.py data_dir --gpu

Predict image class with predict.py along with the probability of that class.

• Basic usage: python predict.py /path/to/image checkpoint

Options:

• Return top KK most likely classes: python predict.py input checkpoint --top_k 3

• Use a mapping of categories to real names: python predict.py input checkpoint --category_names cat_to_name.json

• Use GPU for inference: python predict.py input checkpoint --gpu