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A tutorial for students that surveys basic ML techniques in ipython notebook format.

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AI for Science Tutorial at Argonne National Laboratory

This tutorial is aimed at students who are interested in learning about Machine Learning techniques. The tutorial relies on IPyhton Notebooks which are targeted for running on Google's Colaboratory Platform. This platform gives the user a virtual machine in which to run python codes including machine learning codes. The VM comes with a preinstalled environment that includes most of what is needed for these tutorials.

Before You Arrive

Do the following before you come to the tutorial:

  • You need a Google Account to use Colaboratory
  • Goto Google's Colaboratory Platform
  • You should see this page start_page
  • Click on the New Python 3 Notebook - it may say Python 2 but just click the drop down arrow and select the Python 3 option.
  • Now you will see a new notebook where you can type in python code. clean_page
  • After you enter code, type <shift>+<enter> to execute the code cell.
  • A full introduction to the notebook environment is out of scope for this tutorial, but many can be found with a simple google search
  • We will be using notebooks from this repository during the tutorial, so you should be familiar with how to import them into Colaboratory
  • Now you can open the File menu at the top left and select Open Notebook which will open a dialogue box.
  • Select the GitHub tab in the dialogue box.
  • From here you can enter the url for the github repo: https://github.com/argonne-lcf/AI4ScienceTutorial.git and hit <enter>. open_github
  • This will show you a list of the Notebooks available in the repo.
  • Select the introduction.ipynb file to open and work through it.
  • As each session of the tutorial begins, you will simply select the corresponding notebook from this list and it will create a copy for you in your Colaboratory account (all *.ipynb files in the Colaboratory account will be stored in your Google Drive).

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A tutorial for students that surveys basic ML techniques in ipython notebook format.

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