Pokročilý Machine Learning v Pythone

5h 21min
Time
40
Chapters
Programovanie
Category
5.0
Rating
Expert
Level
slovak
Language

Chapters

Vitajte v kurze
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Materiály na stiahnutie
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Distance-based learning: Algoritmy založené na meraní vzdialeností
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Numerické atribúty a ich základné merania vzdialeností
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Numerické atribúty a pokročilé merania vzdialeností
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Merania vzdialeností pre kategorické atribúty
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Bonusová prednáška pre kategorické atribúty
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Problém zmiešaných vstupných atribútov
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Štandardné riešenia pre zmiešané vstupné atribúty
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Kreatívne riešenia zmiešnach vstupných atribútov
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Textové atribúty
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Nevybalansované dáta
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Problém nevybalansovaných dát
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Vyhodnotenie modelov s nevybalansovanými dátami: Ktoré metriky použiť?
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Ako môžeme vyriešiť problém nevybalansovaných dát?
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"Naivné" sampling metódy
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Úvod do Informovaných sampling metód
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Informovaný Oversampling
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Informovaný Undersampling
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Ensemble modely
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Wisdom of the crowds: "Múdrosť davov"
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Diverzita a kombinovanie predpovedí
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Štandardné prístupy Ensemble modelov
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Bagging modely
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Špeciálny prípad: RandomForest Ensemble
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Špeciálny prípad: ExtraTrees Ensemble
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Pripomeňme si odporúčania na Feature Engineering
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Isolation Forest
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Boosting modely: AdaBoost
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Gradient Boosting Machines
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XGBoost (Extreme Gradient Boosting)
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LightGBM
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CatBoost
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Stacking modely: Soft Voting
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Dynamické budovanie Ensemble modelu: Dynamic Ensemble Building
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Stacked Generalization
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Deep Ensemble modely
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Dynamic Ensemble modely
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Snapshot Ensembling
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Model Distillation
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12 Online courses
1 Posts