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util
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00 Data Preprocessing.ipynb
01 Python Refresher.ipynb
02 Clustering.ipynb
03 Classification.ipynb
04 Regression & Comparing Models.ipynb
05 Recap.ipynb
LICENSE
README.md
faq.md
syllabus.md

README.md

scikit-learn-tutorial

Date/Time/Venue

This tutorial will be held at the Broad Institute. Details:

  • Date: 8 Feb 2016
  • Time: 1 pm - 3 pm
  • Address: 415 Main Street, Cambridge, MA
  • Room: 2nd Floor - one of Monadnock or Yellowstone
  • Registration: on EventBrite
  • Equipment: Bring your laptop and follow the pre-tutorial instrutions below.
  • Help Needed? Contact Eric Ma if you have any issues setting up your computing environment.

Pre-Tutorial Instructions

Ensure that you have the following Python packages installed:

  • Python 3.5
  • scikit-learn
  • biopython
  • jupyter (previously known as the IPython notebook)
  • matplotlib
  • numpy
  • pandas
  • seaborn

An easy way to obtain Python, and the associated packages, is to download the Anaconda distribution here.

Additionally, we will make use of this Github repository. Be sure to have the link handy. Having git is helpful, but optional.

Todo List

  • Make a test script to verify that the environment is setup correctly.