Link
Embed
Share
Beginning
This slide
Copy link URL
Copy link URL
Copy iframe embed code
Copy iframe embed code
Copy javascript embed code
Copy javascript embed code
Share
Tweet
Share
Tweet
Slide 1
Slide 1 text
No content
Slide 2
Slide 2 text
No content
Slide 3
Slide 3 text
Hi Iβm Landon πβ Senior Monkey Patcher @testdouble
Slide 4
Slide 4 text
@thedayisntgray Linkedin Mastodon Twitter Senior Software Consultant @testdouble
Slide 5
Slide 5 text
There was a question that plagued meβ¦ π€
Slide 6
Slide 6 text
No content
Slide 7
Slide 7 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 8
Slide 8 text
But before thatβ¦ π¨ π
Slide 9
Slide 9 text
Jupyter Notebook + iruby
Slide 10
Slide 10 text
No content
Slide 11
Slide 11 text
No content
Slide 12
Slide 12 text
Libraries π
Slide 13
Slide 13 text
require 'numo/narray' require 'daru' require 'rumale'
Slide 14
Slide 14 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 15
Slide 15 text
π©
Slide 16
Slide 16 text
π‘ Max Temperature
Slide 17
Slide 17 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 18
Slide 18 text
No content
Slide 19
Slide 19 text
No content
Slide 20
Slide 20 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 21
Slide 21 text
No content
Slide 22
Slide 22 text
5 Core Values: PRCP = Precipitation SNOW = Snowfall SNWD = Snow depth TMAX = Maximum temperature TMIN = Minimum temperature
Slide 23
Slide 23 text
No content
Slide 24
Slide 24 text
Clean Up Data β Handling Missing values β Outliers β Malformed Data β Eliminate duplicate values
Slide 25
Slide 25 text
Clean Up Data
Slide 26
Slide 26 text
Whoβs Tired πͺ
Slide 27
Slide 27 text
80/20 Rule
Slide 28
Slide 28 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 29
Slide 29 text
Split the data Training Test Dataset
Slide 30
Slide 30 text
No content
Slide 31
Slide 31 text
Linear regression - is an attempt to model the relationship between two variables by fitting a linear equation to the observed data.
Slide 32
Slide 32 text
Y = mx + b
Slide 33
Slide 33 text
f(x) = mx + b
Slide 34
Slide 34 text
No content
Slide 35
Slide 35 text
Best Fit Line
Slide 36
Slide 36 text
Train Model
Slide 37
Slide 37 text
π
Slide 38
Slide 38 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 39
Slide 39 text
No content
Slide 40
Slide 40 text
β Problem β Collect Data β Data Preparation β Train Model β Make Predictions
Slide 41
Slide 41 text
Thank You!
Slide 42
Slide 42 text
π
Slide 43
Slide 43 text
https://tinyurl.com/y8anhkrv Repository
Slide 44
Slide 44 text
No content