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Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Fundamentals of Supervised Machine Learning : With Applications in Python, R, and Stata / Giovanni Cerulli
| Fundamentals of Supervised Machine Learning : With Applications in Python, R, and Stata / Giovanni Cerulli |
| Autore | Cerulli, Giovanni |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xxiv, 391 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68-XX - Computer science [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 68T07 - Artificial neural networks and deep learning [MSC 2020] |
| Soggetto non controllato |
Artificial Neural Networks
Classification Deep Learning Discriminant Analysis Machine Learnig Applications in Medicine and Epidemiology Machine Learning Applications in the Social Sciences Machine learning Model selection Nearest Neighbors Nonparametric Fitting Ontology of Machine Learning Python R software Regularization Sentiment analysis Statistical learning Statistics Supervised machine learning Support Vector Machines Trees |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00278813 |
Cerulli, Giovanni
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| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||