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Data Science
Kapitel 1: Einführung in Data Science
Kapitel 2: Programmiergrundlagen für Data Science
Kapitel 3: Data Acquisition und Cleaning
Kapitel 4: Exploratory Data Analysis (EDA)
Kapitel 5: Data Visualization
Kapitel 6: Feature Engineering
Kapitel 7: Grundlagen des Machine Learning
Kapitel 8: Supervised Learning
Kapitel 9: Unsupervised Learning
Kapitel 10: Geographische Analyse
Kapitel 11: Fortgeschrittene Themen
Kapitel 12: Data Science in der Praxis

Books

Data Science

Kapitel 3: Data Acquis...

Data Cleaning Techniken

Data Cleaning Techniken

Datenquellen und -formate

Bewertung der Data Quality

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