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Machine Learning in Production

This repository contains the resources students need to follow along with the instructor teaching this course in addition to the various labs and their solutions.

There are two means by which to get started (with and w/o Databricks Repos).

Besides the instructions provided here, your instructor will review these procedures at the start of the course.

Getting Started with Databricks Repos

  1. Click on the Repos icon in the navigational pane to the left
  2. By default, you should be in the folder /Repos/your-email-address as in /Repos/student@example.com
  3. Click the Add Repo button above the two swim lanes
  4. In the Add Repo dialog box
    • Select Clone remote Git repo
    • Enter the URL for the Git repo
    • The Git provider GitHub should be selected for you automatically
    • The Repo name should be defaulted to the name of this repo - feel free to rename this if you like
    • Click the Create button
  5. Once the import is done, select the repo folder for this course to view this course's notebooks.
  6. From here you should be able to follow along with your instructor

Getting Started without Databricks Repos (using DBC)

  1. Under Releases in the pane to the right, click on the Latest link
  2. Under Assets look for the link to the DBC file
  3. Right click the DBC file's link and copy the link location (there is no need to download this file)
  4. Back in Databricks, click on the Workspace icon in the navigational pane to the left
  5. In the Workspace swimline, click the Home button to open your home folder - it should open the folder /Users/your-email-address as in /Users/student@example.com
  6. In the swimlane for your email address, click on the down chevron and select Import
  7. In the Import Notebooks dialog
    • Select URL
    • Paste in the URL copied in step #3 above
    • Click Import
  8. Once the import is done, select the repo folder for this course to view this course's notebooks.
  9. From here you should be able to follow along with your instructor

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Machine Learning in Production

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