As we saw in the previous section, Databricks offers a free community edition version of the data science ecosystem for running experiments in notebooks. If you don't already have an account, you can sign up for a free account and start running the notebooks for the course. Once you've logged in, you see a page similar to this. On the left hand side, there's a tab with various options for your home, your recent documents, your clusters, and so on. If you'd like a tour of the ecosystem, click on the button that says Explore the QuickStart tutorial. Next to it, you have an option to import and export data and to the right side, you have the ability to create a blank notebook. Beneath that, there are various options for creating a notebook, creating a table, a new cluster, importing a library, and so on. You can import a notebook into your workspace using the tab on the left. If you click on "Home" and then "Users" and your "Username", you'll be presented with an option from the drop down menu to import a notebook. You can import a notebook, either from a file on your desktop or from a URL. You have the option to drop your file here or to navigate your folder structure to locate the file. Once you've successfully imported the file, you'll see a screen similar to this, whether it's a green checkmark next to your file. Now, that we have imported the notebook, we need to set up a cluster so we can run our code. Once you're on the cluster page that you can get to by selecting the tab on the left here, you'll be presented with various options for a database, one time version. Select one that is a machine learning at one time, preferably one that's recent. Once that's launched, you should see a green circle next to the cluster name. If you click the button here for Clusters, you can also see or check on the status of the available clusters that you created. If any libraries were installed, they would show up here under the Libraries tab. Assuming that you did not install any libraries during the creation of the cluster, let's go ahead and install a Python library after the creation of the cluster. You would notice that there is actually a button that has been installed new, click on that. Once you do that, you'll be presented with the screen similar to this or you can go out and specify a name of a Python library along with the version. I would definitely encourage you to specify the version of the library explicitly to avoid library complex, click "Install" and the library will be installed into your cluster. Now, that your cluster is up and running, click on the "Workspace" tab and select the notebook that you've uploaded. You notice on the top left corner that it says it is attached or not attached to any running clusters. Click on the drop down menu and select a cluster that we've just created. Now, your notebook is attached to a running cluster and ready for execution. I would encourage you to explore the menu structure here and get familiar with the database interface. To execute any of these cells, select the cell, go to the right hand corner and click on the button that looks like a Play button. From the drop down menu, click on one cell to execute that cell. Lastly, I want to point out that Databricks allows you to integrate your GitHub repositories with the Databricks ecosystem so as to brush and control your notebooks.
