Vladimir Alekseichenko podczas AIMeetup #3 w Krakowie organizowanego przez 2040.io opowiadał o tym jak uczenie maszynowe istotnie wpływa na nasze życie już teraz i jak jeszcze bardziej wpłynie życie na naszych dzieci czy wnuków.
11. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
12. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
17. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
18. Wytworzenie cech
(feature engineering)
• ilościowe => od 1 do 10, 11 do 20…
• daty => dzień, miesiąc, rok, godzina, czy weekend…
• kategorii/jakościowe (czerwony, zielony, biały)
• przypisać identyfikator liczbowy (1, 2, 3)
• stworzyć n-kolumn binarnych (jest czerwony? itd)
• prawdopodobieństwa ze zmienną docelową
19.
20. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
21. Selekcja cech
(feature selection)
• Czym mniej tym lepiej (prostszy model)
• Zostawić najbardziej wartościowe (idealnie jedna :)
• Cechy (zazwyczaj) są zależny, więc trzeba uważać… (sprawdzać empirycznie)
• Szybciej
24. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
32. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
35. Understand
Business & Data
Read and explore data
Feature Engineering
Create a new ones based on already exists
Feature Selection
Select only useful features
Model Selection
Find the best model(s) model
A
model
B
model
C
model
D
model
E
Tuning
Hyperparameters
Find the best hyperparameters for given model
Ensemble Modeling
Combine few models into one more better
x0.6 x0.4+
mode
l B
mode
l E
datetime season temp count
2011-01-01 08:32:02 1 9.23 5
2012-04-02 12:10:00 2 18.78 32
2012-08-07 15:47:01 3 15.45 15
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708
mode
l B
mode
l E
datetime season temp hour day month … count count_log
2011-01-01
08:32:02 1 9.23 8 1 1 … 5 1.609
2012-04-02
12:10:00 2 18.78 12 2 4 … 32 3.466
2012-08-07
15:47:01 3 15.45 15 7 8 … 15 2.708