How to Prepare a Linode for Data Science with a Single Command!

In the world of data science, having access to reliable computing resources is essential. Linode offers Virtual Private Servers (VPS), or “Linodes”, that can be a cost-effective solution for running data science workloads in the cloud, even if you don't have access to a GPU. In this article, we'll walk you through the process of setting up a Linode for data science and installing a few popular deep learning frameworks like TensorFlow, Keras, and PyTorch on a CPU-only Linode instance.

Prerequisites

Before we get started, you'll need the following:

1. Linode Account: Sign up for a Linode account if you don't already have one.

2. Linode VPS: Create a secured Linode VPS instance with your desired specifications. For this tutorial, we'll assume you're using the latest Ubuntu as your operating system.

3. Remote Access: Ensure you have SSH or LISH Console access to your Linode.

Connecting to Your Linode

Once your instance is up and running, connect to it using SSH:

ssh your_username@your_linode_ip

Replace your_username with your Linode username and your_linode_ip with your Linode’s IP address.

For LISH, simply click "Launch LISH Console" in Cloud Manager, then log in.

Installing Everything with One Command

Since our chosen frameworks are all installed through pip, you can streamline the installation process by combining all the steps into a single command. Here's the one-liner that updates packages, installs Python, and the handful of deep learning frameworks:

sudo apt update && sudo apt upgrade -y && sudo apt install python3 python3-pip -y && pip3 install tensorflow keras torch

This command will:

• Update package lists and upgrade existing packages.
• Install Python and pip.
• Install TensorFlow, Keras, and PyTorch using pip.

Testing the Frameworks

After installation, you should test each framework to ensure it's working correctly. You can find example code and tutorials on their respective official websites and documentation.

https://www.tensorflow.org/
https://keras.io/
https://pytorch.org/

Conclusion

Setting up a Linode for data science with deep learning frameworks like TensorFlow, Keras, and PyTorch is a practical way to get started with your data science projects. Remember to monitor your Linode's resource usage to ensure it meets your needs and consider upgrading to a GPU-based instance if your workloads require more computational power. Just know that GPU-based Linodes will require Nvidia CUDA.

Is there a minimum recommended plan to efficiently run Keras, Tensorflow, and PyTorch for inference ?