Libro adottato a Politecnico di Milano, a.a. 2026/2027 · 5 canali
«Mohammed – Zaki and Wagner Meira» è adottato per Data Mining dal prof. Pierluca Lanzi (Computer Science and Engineering – Politecnico di Milano); per Data Mining dal prof. Daniele Loiacono (Engineering Physics, Geoinformatics Engineering, Mathematical Engineering e altri corsi – Politecnico di Milano).
Come lo indica il docente: Mohammed J. Zaki and Wagner Meira, Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms (Second Edition), Cambridge University Press, Anno edizione: 2020, ISBN: 978-1108473989 Note: Freely available at http://www.dataminingbook.info/
ISBN
9781108473989
Chi lo adotta
Data Mining – Prof. Pierluca Lanzi (canale unico)Computer Science and Engineering · Laurea triennale · 2º anno · 1º semestre · ARTIFICIAL INTELLIGENCE · 5 CFU
Argomenti del programma: Introduction to Data Mining Data representation Text representation and embeddings Data exploration and visualization Association rules Clustering - Hierarchical - Representation-based - Density-based Regression Classification - Logistic regression - Naive Bayes and Bayesian Belief Network - k-nearest neighbor - Decision trees - Ensemble methods Advanced Topics - Time series - Anomaly detection - Explainability -…
Argomenti del programma: Introduction to Data Mining Data representation Text representation and embeddings Data exploration and visualization Association rules Clustering - Hierarchical - Representation-based - Density-based Regression Classification - Logistic regression - Naive Bayes and Bayesian Belief Network - k-nearest neighbor - Decision trees - Ensemble methods Advanced Topics - Time series - Anomaly detection - Explainability -…
Argomenti del programma: Introduction to Data Mining Data representation Text representation and embeddings Data exploration and visualization Association rules Clustering - Hierarchical - Representation-based - Density-based Regression Classification - Logistic regression - Naive Bayes and Bayesian Belief Network - k-nearest neighbor - Decision trees - Ensemble methods Advanced Topics - Time series - Anomaly detection - Explainability -…
Argomenti del programma: Introduction to Data Mining Data representation Text representation and embeddings Data exploration and visualization Association rules Clustering - Hierarchical - Representation-based - Density-based Regression Classification - Logistic regression - Naive Bayes and Bayesian Belief Network - k-nearest neighbor - Decision trees - Ensemble methods Advanced Topics - Time series - Anomaly detection - Explainability -…
Argomenti del programma: Introduction to Data Mining Data representation Text representation and embeddings Data exploration and visualization Association rules Clustering - Hierarchical - Representation-based - Density-based Regression Classification - Logistic regression - Naive Bayes and Bayesian Belief Network - k-nearest neighbor - Decision trees - Ensemble methods Advanced Topics - Time series - Anomaly detection - Explainability -…
Libri Universitari