Inhalt - Praxiseinstieg Machine Learning mit Scikit-Learn, Keras und TensorFlow, 2nd Edition [Book]

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Inhalt

Teil IDie Grundlagen des Machine Learning

1Die Machine-Learning-Umgebung

Was ist Machine Learning?

Warum wird Machine Learning verwendet?

Anwendungsbeispiel

Unterschiedliche Machine-Learning-Systeme

Überwachtes/unüberwachtes Lernen

Batch- und Online-Learning

Instanzbasiertes versus modellbasiertes Lernen

Die wichtigsten Herausforderungen beim Machine Learning

Unzureichende Menge an Trainingsdaten

Nicht repräsentative Trainingsdaten

Minderwertige Daten

Irrelevante Merkmale

Overfitting der Trainingsdaten

Underfitting der Trainingsdaten

Zusammenfassung

Testen und Validieren

Hyperparameter anpassen und Modellauswahl

Datendiskrepanz

2Ein Machine-Learning-Projekt von A bis Z

Der Umgang mit realen Daten

Betrachte das Gesamtbild ...

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