at Hochschule Mittweida | Flashcards & Summaries

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Wie erstellt man einen Vektor?

name <-- c(*datensatz)

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie erstellt man einen Vektor?

name <-- c(*datensatz)

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie erstelle ich eine Matrix (aus zwei Vekoren)?

matrixname <-- rbint(v1, v2)

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Wie lege ich die Anzahl der Zeilen und Spalten in einer Matrix fest?

matrixname <-- matrix(datensatz, byrow = n, nrow = n)

byrow ist zeilen

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Was ist maschinelles lernen?

- Konstruktion und Nutzung von Algorithmen die von Daten lernen.

- mehr Informationen führen zu besseren Ergebnissen. (Performance)

- Erfahrung kommt von bereits gelösten Probleminstanzen. (Beispiele)

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie erzeuge ich einen Dataframe?

s.data.frame(matrix, col.names = names(v1,...,vn))

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie überprüfe ich, ob ein Datensatz ein Dataframe ist?

is.data.frame(datensatz)

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Learning-Assistant with spaced repetition algorithm

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie erzeuge ich kategorielle Daten?

factor(datensatz, order = true/false, levels = c())

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Welches Paket enthält die Funktion zur Datenmanipulation?

dplyr

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie bestimme ich die Größe eines Datensatzes?

dim(datensatzname)

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie kann ich die Datenstruktur explorieren?

str(datensatz)

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Learning-Assistant with spaced repetition algorithm

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Wie erstellt man einen Vektor?

name <-- c(*datensatz)

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Big Langeweile at Hochschule Mittweida

Flashcards and summaries for Big Langeweile at the Hochschule Mittweida

Study with flashcards and summaries for the course Big Langeweile at the Hochschule Mittweida

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Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

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Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

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Dorothea Lange at

Biwi M1 Landau at

Big Data at

Big Data at

Big Data at

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Big Langeweile at Hochschule Mittweida

Flashcards and summaries for Big Langeweile at the Hochschule Mittweida

Study with flashcards and summaries for the course Big Langeweile at the Hochschule Mittweida

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Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

Exemplary flashcards for Big Langeweile at the Hochschule Mittweida on StudySmarter:

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Dorothea Lange at

Biwi M1 Landau at

Big Data at

Big Data at

Big Data at

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