About Configuring Your System
Before installing software on your instance, you must configure it to accept traffic over the Internet from your local computer.
After you set up access, install Anaconda and then create the machine learning environments that you'll use.
Set up your Oracle Cloud Infrastructure Compute Instance
Edit the security list for the virtual cloud network that your instance uses, then update the firewall rules for your instance.
You use the security list to specify the traffic that's allowed to flow over the virtual cloud network that your instance uses. After the security list for the network is set up, you must update the firewall rules on your instance to allow access to that traffic. In this case open port 8888, which is the default port for Jupyter Notebook.
It's easiest to use stateful rules. In essence, a stateful rule allows both ingress and egress on the selected port. If you set up a stateless ingress rule, then you must also set up a corresponding egress rule.
Install Anaconda Distribution
Use Anaconda and its package manager to set up and maintain individual machine learning environments on your compute instance.
You can get the latest installer from https://repo.continuum.io/archive/. These instructions assume that the operating system is either Oracle Linux 7.7 or Ubuntu 18.04, and that the version of Anaconda Distribution is 2019.10 with Python 3.7.
Set Up a Machine Learning Sandbox Environment on Oracle Linux
Create a separate sandbox environment and install TensorFlow and Jupyter Notebook.
Create an environment and give it the name sandbox. An environment is isolated from rest of the compute instance so that tools and software that you install into the sandbox environment are specific to the sandbox environment. You can have several environments on one compute instance, each with its own individual configuration.
In the following procedure, you install TensorFlow 2 and Jupyter Notebook, but they are not the only tools available. Anaconda Distribution has over 1,500 machine learning packages that you can install, including scikit-learn, pandas, and RStudio.
Note:
Because the default Python on Oracle Linux is Python 2, you need to make sure that the sandbox environment is created with Python 3 in Step 2. Specify Python 3.7 because at the time of this writing, the latest Tensorflow (2.0.0) does not work with Python 3.8.
If the ingress rules and firewall settings of your instance are correct, you should be able to open Jupyter Notebook in a web browser by navigating to https://<instance-ip-address>:8888
.
Set Up a Machine Learning Sandbox Environment on Ubuntu
Create a separate sandbox environment and install TensorFlow and Jupyter Notebook.
Create an environment and give it the name sandbox. An environment is isolated from rest of the instance so that tools and software that you install into the sandbox environment are specific to the sandbox environment. You can have several environments on one compute instance, each with its own individual configuration.
In the following procedure, you install TensorFlow 2 and Jupyter Notebook, but they are not the only tools available. Anaconda Distribution has over 1,500 machine learning packages that you can install, including scikit-learn, pandas, and RStudio.
If the ingress rules and firewall settings of your instance are correct, you should be able to open Jupyter Notebook in a web browser by navigating to https://<instance-ip-address>:8888
.