[LEADERG AI ZOO] Jupyter-Data-LSTM-PyTorch

Language:

繁體中文

 

 

 

 

[Introduction]

 

 

Use LSTM to train and predict the ticket sales.

 

 

 

[Instructions]

 

 

1. 1_delete_log.ipynb

Delete the old logs file.

 

 

2. 2_train.ipynb

Set the parameters:

• train_input_filename: input data file path

• train_output_filename: the path of the output prediction file

• model_filename: the path of the output model file

• scaler_filename: output normalized file path

• log_path: The log file path of log_path output

• time_seq: the length of the time series

• learning_rate: learning rate

• epochs: the number of epochs

 

 

Set neural network parameters:

• hidden_layer_size: hidden layer neurons

• num_layers: the number of layers of the network

 

 

After the setting is completed, it can be executed.

 

 

 

3. 3_kill_tensorboard.ipynb

Delete the previous tensorboard.

 

 

 

4. 4_tensorboard.ipynb

Start tensorboard.

 

 

 

5. 5_inference.ipynb

Set the parameters parameter:

• inference_input_filename: input data file path

• inference_output_filename: the path of the output prediction file

• model_filename: input model file path

• scaler_filename: input normalized file path

• time_seq: length of time series

 

 

Set neural network parameters:

• hidden_layer_size: hidden layer neurons

• num_layers: the number of layers of the network

 

 

After the setting is completed, it can be executed.

After execution, you can see the result of LSTM inference.

 

 

Jupyter-Data-LSTM-PyTorch-inference.png

 


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