AML at Karlsruher Institut für Technologie

Flashcards and summaries for AML at the Karlsruher Institut für Technologie

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Study with flashcards and summaries for the course AML at the Karlsruher Institut für Technologie

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Bug Data Characteristics

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Volume 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Velocity 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Variety 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Veracity 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Value 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

ML vs statistics 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Random variable 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Variable types 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Nominal variables 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Binary variables 

Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

Ordinal variables

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Exemplary flashcards for AML at the Karlsruher Institut für Technologie on StudySmarter:

AML

Bug Data Characteristics
Volume 
Velocity 
Variety 
Veracity 
Value

AML

Volume 
Volume refers to the amount of Data generated every Second

AML

Velocity 
Velocity refers to the Speed at which the Data are generated every day

AML

Variety 
Types of Data can je categorized into structured, semi structured and unstructured

AML

Veracity 
Veracity is the quality of the data, how accurate are the captured Data and how much noise exist in the data

AML

Value 
The large amount of Data are useless, nur it could be Turned into value 

AML

ML vs statistics 
Focus in predictions vs Focus on the undestanding and Hypothese Testing 

Algorithmus based vs Model based 

No Hypothese and Data are already collected vs First Hypothese then collect the Data 

AML

Random variable 
A random variable assigns a real number to wach outcomes of the random Test 

AML

Variable types 
Nominal 

Binary
 
Ordinal

Numeric

AML

Nominal variables 
Are names of Things or symbols. 
No Order or mathematical Operations

AML

Binary variables 
Nominal variables with only two categories 

AML

Ordinal variables
Variables with meaningfull Order, But Intervalls are unknown 

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Human Computer Interaction (HCI)

Patentrecht

Markenrecht

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Best EdTech Startup in Europe

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EUROPEAN YOUTH AWARD IN SMART LEARNING

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BEST EDTECH STARTUP IN GERMANY

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Best EdTech Startup in Europe

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Awards

EUROPEAN YOUTH AWARD IN SMART LEARNING

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Awards

BEST EDTECH STARTUP IN GERMANY

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