Return to Video

Coding It Up - Intro to Machine Learning

  • 0:00 - 0:04
    Welcome now to the coding portion of the regression lesson.
  • 0:04 - 0:10
    We start, as always, on Google and we look for what sklearn has to offer us.
  • 0:10 - 0:12
    As you can see, there's plenty going on here.
  • 0:12 - 0:16
    This linear regression is what we'll end up using eventually.
  • 0:16 - 0:20
    But I actually think this link is a better one to start at because it
  • 0:20 - 0:24
    gives us a little bit more of an introduction to generalized linear models.
  • 0:24 - 0:28
    So we have here a formula that, it's a little bit hard to tell, but
  • 0:28 - 0:31
    this is just rewriting y equals mx plus b, but
  • 0:31 - 0:36
    now we can have more than one x available to us.
  • 0:36 - 0:38
    We'll get into this a little bit later in the lesson right now,
  • 0:38 - 0:40
    but at least this tells us that we're in the right place for
  • 0:40 - 0:44
    something that has a linear form to it.
  • 0:44 - 0:47
    Scrolling down a little bit, I see something called ordinary least squares.
  • 0:47 - 0:48
    The exact name for
  • 0:48 - 0:53
    the code is linear regression, and this looks like exactly what I want.
  • 0:53 - 0:55
    I have a variety of points.
  • 0:55 - 0:57
    I'm fitting them with a line.
  • 0:57 - 1:00
    And maybe even better, I have some example code that can get me started.
  • 1:00 - 1:04
    I hope you recognize that the code here really isn't all that different
  • 1:04 - 1:08
    from the types of codes that we were seeing for the supervised classifiers.
  • 1:08 - 1:10
    So that means that we start with an import statement,
  • 1:10 - 1:13
    from sklearn import linear_model.
  • 1:13 - 1:18
    Within linear_model, there's an object called linearRegression and
  • 1:18 - 1:20
    we use that to create our classifier.
  • 1:20 - 1:22
    The next thing that we do is we fit our classifier.
  • 1:22 - 1:24
    And then here,
  • 1:24 - 1:28
    they're not making predictions with it, although we'll be doing that as well.
  • 1:28 - 1:31
    What they're doing here is they're reading out the coefficients, or
  • 1:31 - 1:33
    what we called the slope.
  • 1:33 - 1:37
    Scrolling down a little further, I see that there's a more detailed example here
  • 1:37 - 1:39
    that I could use to help me if I get stuck anywhere.
  • 1:40 - 1:43
    But as it happens, this is going to be enough to get us off the ground.
Title:
Coding It Up - Intro to Machine Learning
Description:

more » « less
Video Language:
English
Team:
Udacity
Project:
ud120 - Intro to Machine Learning
Duration:
01:44
Udacity Robot edited English subtitles for 06-31 Coding_It_Up
Udacity Robot edited English subtitles for 06-31 Coding_It_Up
Cogi-Admin edited English subtitles for 06-31 Coding_It_Up

English subtitles

Revisions Compare revisions