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Python for Probability, Statistics, and Machine Learning [[electronic resource] /] / by José Unpingco
| Python for Probability, Statistics, and Machine Learning [[electronic resource] /] / by José Unpingco |
| Autore | Unpingco José <1969-> |
| Edizione | [3rd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (524 pages) |
| Disciplina | 006.31 |
| Soggetto topico |
Telecommunication
Computer science - Mathematics Mathematical statistics Engineering mathematics Engineering - Data processing Statistics Data mining Communications Engineering, Networks Probability and Statistics in Computer Science Mathematical and Computational Engineering Applications Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Data Mining and Knowledge Discovery Python (Llenguatge de programació) Aprenentatge automàtic Probabilitats Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031046483
9783031046476 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Part 1 Getting Started with Scientific Python -- Installation and Setup -- Numpy -- Matplotlib -- Ipython -- Jupyter Notebook -- Scipy -- Pandas -- Sympy -- Interfacing with Compiled Libraries -- Integrated Development Environments -- Quick Guide to Performance and Parallel Programming -- Other Resources -- Part 2 Probability -- Introduction -- Projection Methods -- Conditional Expectation as Projection -- Conditional Expectation and Mean Squared Error -- Worked Examples of Conditional Expectation and Mean Square Error Optimization -- Useful Distributions -- Information Entropy -- Moment Generating Functions -- Monte Carlo Sampling Methods -- Useful Inequalities -- Part 3 Statistics -- Python Modules for Statistics -- Types of Convergence -- Estimation Using Maximum Likelihood -- Hypothesis Testing and P-Values -- Confidence Intervals -- Linear Regression -- Maximum A-Posteriori -- Robust Statistics -- Bootstrapping -- Gauss Markov -- Nonparametric Methods -- Survival Analysis -- Part 4 Machine Learning -- Introduction -- Python Machine Learning Modules -- Theory of Learning -- Decision Trees -- Boosting Trees -- Logistic Regression -- Generalized Linear Models -- Regularization -- Support Vector Machines -- Dimensionality Reduction -- Clustering -- Ensemble Methods -- Deep Learning -- Notation -- References -- Index. |
| Record Nr. | UNISA-996499872203316 |
Unpingco José <1969->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Python for Probability, Statistics, and Machine Learning / / by José Unpingco
| Python for Probability, Statistics, and Machine Learning / / by José Unpingco |
| Autore | Unpingco José <1969-> |
| Edizione | [3rd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (524 pages) |
| Disciplina |
006.31
005.133 |
| Soggetto topico |
Telecommunication
Computer science - Mathematics Mathematical statistics Engineering mathematics Engineering - Data processing Statistics Data mining Communications Engineering, Networks Probability and Statistics in Computer Science Mathematical and Computational Engineering Applications Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Data Mining and Knowledge Discovery Python (Llenguatge de programació) Aprenentatge automàtic Probabilitats Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031046483
9783031046476 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Part 1 Getting Started with Scientific Python -- Installation and Setup -- Numpy -- Matplotlib -- Ipython -- Jupyter Notebook -- Scipy -- Pandas -- Sympy -- Interfacing with Compiled Libraries -- Integrated Development Environments -- Quick Guide to Performance and Parallel Programming -- Other Resources -- Part 2 Probability -- Introduction -- Projection Methods -- Conditional Expectation as Projection -- Conditional Expectation and Mean Squared Error -- Worked Examples of Conditional Expectation and Mean Square Error Optimization -- Useful Distributions -- Information Entropy -- Moment Generating Functions -- Monte Carlo Sampling Methods -- Useful Inequalities -- Part 3 Statistics -- Python Modules for Statistics -- Types of Convergence -- Estimation Using Maximum Likelihood -- Hypothesis Testing and P-Values -- Confidence Intervals -- Linear Regression -- Maximum A-Posteriori -- Robust Statistics -- Bootstrapping -- Gauss Markov -- Nonparametric Methods -- Survival Analysis -- Part 4 Machine Learning -- Introduction -- Python Machine Learning Modules -- Theory of Learning -- Decision Trees -- Boosting Trees -- Logistic Regression -- Generalized Linear Models -- Regularization -- Support Vector Machines -- Dimensionality Reduction -- Clustering -- Ensemble Methods -- Deep Learning -- Notation -- References -- Index. |
| Record Nr. | UNINA-9910629298103321 |
|
Unpingco José <1969->
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Python programming for data analysis / / José Unpingco
| Python programming for data analysis / / José Unpingco |
| Autore | Unpingco José <1969-> |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XII, 263 p. 134 illus., 123 illus. in color.) |
| Disciplina | 005.133 |
| Soggetto topico | Python (Computer program language) |
| ISBN | 3-030-68952-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Basic Language -- Basic Data Structures -- Basic Programming -- File Input/Output -- Dealing with Errors -- Power Python Features to Master -- Advanced Language Features -- Using modules -- Object oriented programming -- Debugging from Python -- Using Numpy – Numerical Arrays in Python -- Data Visualization Using Python -- Bokeh for Web-based Visualization -- Getting Started with Pandas -- Some Useful Python-Fu -- Conclusion. |
| Record Nr. | UNINA-9910483273203321 |
|
Unpingco José <1969->
|
||
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||