March 3: Data, models, errors Questions for today How can we - - PowerPoint PPT Presentation

march 3 data models errors
SMART_READER_LITE
LIVE PREVIEW

March 3: Data, models, errors Questions for today How can we - - PowerPoint PPT Presentation

March 3: Data, models, errors Questions for today How can we filter a pandas data frame? Why are squared errors important, and how do they relate to the normal distribution and log likelihood? How can we predict one variable given


slide-1
SLIDE 1

March 3: Data, models, errors

slide-2
SLIDE 2

Questions for today

  • How can we filter a pandas data frame?
  • Why are squared errors important, and how do they

relate to the normal distribution and log likelihood?

  • How can we predict one variable given another?

What makes avocados cost more or less?

  • How do we compare predictive models?
slide-3
SLIDE 3

Questions for today

  • How can we filter a pandas data frame?
  • Why are squared errors important, and how do they

relate to the normal distribution and log likelihood?

  • How can we predict one variable given another?

What makes avocados cost more or less?

  • How do we compare predictive models?
slide-4
SLIDE 4
slide-5
SLIDE 5
slide-6
SLIDE 6
slide-7
SLIDE 7
slide-8
SLIDE 8
slide-9
SLIDE 9
slide-10
SLIDE 10
slide-11
SLIDE 11
slide-12
SLIDE 12
slide-13
SLIDE 13

Questions for today

  • How can we filter a pandas data frame?
  • Why are squared errors important, and how do they

relate to the normal distribution and log likelihood?

  • How can we predict one variable given another?

What makes avocados cost more or less?

  • How do we compare predictive models?
slide-14
SLIDE 14
slide-15
SLIDE 15
slide-16
SLIDE 16
slide-17
SLIDE 17
slide-18
SLIDE 18
slide-19
SLIDE 19
slide-20
SLIDE 20
slide-21
SLIDE 21
slide-22
SLIDE 22