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Jupyter Notebooks for Adv. Predictive Modeling Course
Jupyter Notebook
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Welcome to the UCI Data Science Initiative's Advanced Predictive Modeling with Python course! This repository contains the Jupyter (formerly iPython) Notebooks we'll be using throughout the course. Here are the steps to get started:

  1. Should be installed from taking first Predictive Modeling course: If you haven't done so already, download and install the Anaconda Scientific Python Distribution version 2.7. If it offers to make itself your default Python distribution, allow it.
  2. Whether you've just installed Anaconda, or you have done so previously, you should now update Anaconda to the latest version of the distribution. It changes a lot so do this today even if you did recently.
  3. Open a terminal or command prompt.
  4. Type conda update conda and press enter or return. Confirm that you'd like it to make any changes that it offers.
  5. Download the code repository.
  6. Click here to download a zip file containing this entire repository.
  7. Unzip that file into a directory you know how to find; you'll need it several times throughout the day.
  8. Start a jupyter notebook server.
  9. Open a terminal and type jupyter notebook. Navigate to the directory where you unzipped this repository.
  10. Open "Test Notebook.ipynb".
  11. Click "Cell" at the top of the opened notebook, followed by "Run All" and ensure that 1) there are no errors and that 2) the output from the first cell is the same as that in the second. If the notebook seems busy / unresponsive, SciKit-Learn is downloading some of the datasets we'll be using. This can take several minutes; the download size is about 200 MB.
  12. If everything looks good, close the browser tab containing the test notebook but keep open the tab listing all the other notebooks.

There are two sets of notebooks. The ones you see above (in the repository's root) are incomplete, ready to be filled-in by the course's participants. In the Solutions directory, you'll find the completed versions.

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