Jacobucci (49 risultati)

Soft cover. Condizione: Good. 1st Edition. Binding has wear; interior has light wear; tight, text clean. Paginated 263-318, illustrated. [br 3].

paperback. Condizione: Fine.

Condizione: As New. Unread book in perfect condition.

Condizione: buono. Architettura Fine arts Architecture bross. edit. ill. fuori catalogo.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Paperback. Condizione: new. Paperback. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New.

Condizione: Buone. italiano Condizioni dell'esterno: logorata e macchiata Condizioni dell'interno: Ottime.

Condizione: New.

Paperback. Condizione: New. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. …

Paperback. Condizione: New. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. …

Paperback. Condizione: New.

Condizione: New. In English.

Condizione: DISCRETO USATO. I ED. Da revisionare ITALIANO Coperta minimente imbrunita e con ordinari segni del tempo. Tagli regolari ed imbruniti, pagine ben salde alla costa e con imbrunitura. Libro completamente fruibile, con introduzione dell'autore e con una testimonianza di Jorge Luis Borges (traduzione di Marisa Lago Vajarini approvata dall'autore), presenti numerose illustrazioni in nero fuori testo, prima edizione, numero pagine 381.…

Condizione: As New. Unread book in perfect condition.

Condizione: New. 2023. 1st Edition. Paperback. . . . . .

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Paperback. Condizione: Brand New. 408 pages. 9.75x7.00x0.75 inches. In Stock.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Hardcover. Condizione: Tadellos. Condizione sovraccoperta: Tadelloser Umschlag. Leichte Lagerspuren, sonst tadellos.

Condizione: As New. Unread book in perfect condition.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. 2023. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Condizione: NEW.

Condizione: New.

Paperback. Condizione: new. Paperback. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…