Introduction to Machine learning with scikit-learn

Sep 6, 2019

10:00 am - 6:00 pm

Instructors: Andreas Müller

Helpers: Sandeep Namburi, Daniel Danis, Anne Deslattes Mays, Jim Kadin, Joshy George

General Information

Where: The Jackson Laboratory for Genomic Medicine, Holt Conference Room & Room 2440, 10 Discovery Dr, Farmington CT. Get directions with OpenStreetMap or Google Maps.

When: Sep 6, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have a few specific software packages installed (listed below).

Code of Conduct: Everyone who participates is required to conform to the Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email susan.mcclatchy@jax.org for more information.

Surveys

Please be sure to complete this survey after the workshop.

Post-workshop Survey

Schedule

Friday, Sep 6

Before Setup
10:00 Welcome and introduction
10:30 Supervised Learning
11:00 Preprocessing
11:30 Missing Values
12:25 Obtain afternoon materials
12:30 Lunch break
13:30 Grid search and cross-validation
14:45 Coffee
15:00 Linear models for classification
15:45 Linear models for regression
16:30 Decision trees
17:45 Post-workshop survey
18:00 END

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.

Syllabus

Setup

Please see software installation instructions below. In addition, please prepare for this workshop by cloning the GitHub repository if you are familiar with command line git. This is highly encouraged as it allows you to easily synchronize any changes to the material.

git clone https://github.com/amueller/ml-workshop-1-of-4.git

If you are not familiar with git, you can download the repository as a .zip file by heading over to the GitHub repository in your browser and click the green Download button in the upper right. After obtaining the material, open and execute a Jupyter Notebook jupyter notebook check_env.ipynb that is located at the top level of this repository. Inside the repository, you can open the notebook by executing

jupyter notebook check_env.ipynb

inside this repository. Inside the Notebook, you can run the code cell by clicking on the Run Cells button.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Video Tutorial
  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select "Use the nano editor by default" and click on "Next".
    3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
    4. Click on "Next".
    5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
    6. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  3. If your "HOME" environment variable is not set (or you don't know what this is):
    1. Open command prompt (Open Start Menu then type cmd and press [Enter])
    2. Type the following line into the command prompt window exactly as shown:

      setx HOME "%USERPROFILE%"

    3. Press [Enter], you should see SUCCESS: Specified value was saved.
    4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on macOS and Linux is usually set to Vim, which is not famous for being intuitive. If you accidentally find yourself stuck in it, hit the Esc key, followed by :+Q+! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

nano is a basic editor and the default that instructors use in the workshop. It is installed along with Git.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.

Others editors that you can use are BBEdit or Sublime Text.

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.

Python

Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

  1. Open https://www.anaconda.com/download/#linux with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type 
    bash Anaconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with: 
    cd Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.