Revision history [back]

To connect the local Jupyter book to the school server for training models, follow these steps:

1. Connect to the school server: Firstly, connect to the school server by opening a terminal and using the SSH command to connect to the server.

2. Create a virtual environment: Create a virtual environment on the school server for installing the required packages for training models.

3. Install the required packages: Install the required packages for training models, such as NumPy, Pandas, Scikit-learn, TensorFlow, Keras, or PyTorch.

4. Start the Jupyter notebook: Start the Jupyter notebook on the school server and get the access URL.

5. Access the Jupyter notebook remotely: From your local machine, open a web browser and enter the access URL of the Jupyter notebook on the school server. This will connect the local Jupyter book to the school server for training models.

6. Upload the data: Upload the required data for training models to the school server.

7. Train the models: Use the Jupyter notebook to train the models on the school server.

8. Download the trained models: Once the models are trained, download them from the school server to your local machine for further analysis.

Note: Ensure that you have the necessary permissions to connect to the school server and install packages on it.