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Aus Daten Lernen: Statistisches maschinelles Lernen mit Python: Regression, Klassifizierung und neuronale Netze
Paperback
Publisher: Independently Published
Published: Jul 16 2026
Pages: 260
Weight: 0.70
Height: 0.65 Width: 6.00 Depth: 9.00
Language: German
AUS DATEN LERNEN ist ein praxisorientiertes Fachbuch für Entwickler, Data Scientists und Ingenieure, die maschinelles Lernen nicht nur anwenden, sondern wirklich verstehen und systematisch aufbauen möchten.
Dieses Buch führt dich in die Grundlagen und fortgeschrittenen Konzepte des statistischen maschinellen Lernens mit Python ein. Der Fokus liegt auf dem Verständnis der mathematischen und datengetriebenen Prinzipien hinter modernen KI-Systemen - nicht nur auf der Nutzung fertiger Bibliotheken.
Du lernst, wie aus Daten funktionierende Modelle entstehen, die Vorhersagen treffen, Muster erkennen und komplexe Zusammenhänge abbilden.
Im Mittelpunkt stehen drei Kernbereiche:
- Regression zur Modellierung kontinuierlicher Zusammenhänge
- Klassifikation zur strukturierten Entscheidungsfindung
- Neuronale Netze als Grundlage moderner KI-Systeme
Du lernst unter anderem:
- Wie Daten vorbereitet, bereinigt und analysiert werden
- Wie lineare und nichtlineare Modelle in Python implementiert werden
- Wie Klassifikationsprobleme systematisch gelöst werden
- Wie neuronale Netze funktionieren und trainiert werden
- Wie Modelle bewertet, validiert und optimiert werden
- Wie Overfitting und Underfitting erkannt und verhindert werden
- Wie statistische Grundlagen direkt auf Machine Learning angewendet werden
Praxisnahe Beispiele und verständliche Erklärungen verbinden Theorie und Anwendung, sodass du eigene ML-Modelle sicher entwickeln und verbessern kannst.
Ob Forschung, Data Science, Automatisierung oder KI-Entwicklung - dieses Buch vermittelt die Fähigkeiten, um Daten in echte Entscheidungen zu verwandeln.
AUS DATEN LERNEN - Der praxisnahe Einstieg in statistisches maschinelles Lernen mit Python, Regression, Klassifikation und neuronalen Netzen.
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