Kestemont (90 risultati)

Condizione: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Condizione: Very Good.

Bulletin de la Société royale de Botanique de Belgique, Tome 105, 1972, Recherches sur l'écosystème forêt, série F : les taillis simples de l'Ardenne, Contribution n° 4, 14 pages agrafées de 18x26 cm Très bon état - Pour les envois hors de France, la tafication «livre & brochure» pour les frais de port a disparue.Les frais de port annoncés correspondent à une moyenne. Ils seront calculés au plus juste en fonction du poids de votre article.…

Bulletin de la Société royale de Botanique de Belgique, Tome 105, 1972, Comité national belge du programme biologique international - sections PT & PF, Projet Mirwart (Province de Luxembourg), Contribution n° 2, 14 pages agrafées de 18x26 cm Très bon état - Pour les envois hors de France, la tafication «livre & brochure» pour les frais de port a disparue.Les frais de port annoncés correspondent à une moyenne. Ils seront calculés au plus juste en fonction du poids de votre article.…

hardcover. Condizione: New.

Paperback. Condizione: Brand New. 41 pages. 11.00x8.50x0.10 inches. In Stock.

Paperback. Good; creased spine. Red underlining on pp. 43 & 45. 679 pp.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: Very Good.

Hardback. Condizione: New. A practical guide to data-intensive humanities research using the Python programming languageThe use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment.The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter.An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions.Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of PythonApplicable to many humanities disciplines, including history, literature, and sociologyOffers real-world case studies using publicly available data setsProvides exercises at the end of each chapter for students to test acquired skillsEmphasizes visual storytelling via data visualizations.…

Paperback. Very good; creased spine. 679 pp.

Broché. Condizione: Bon État. 40 pages en format 16 - 24 cm - exercices.

broché Bristol illustré. Condizione: Très Bon État. 167 pages en format grand -8--- TBE.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

broché Bristol. Condizione: Bon État. 93 pages en format 16 - 24 cm.

Hardback. Condizione: New. A practical guide to data-intensive humanities research using the Python programming languageThe use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment.The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter.An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions.Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of PythonApplicable to many humanities disciplines, including history, literature, and sociologyOffers real-world case studies using publicly available data setsProvides exercises at the end of each chapter for students to test acquired skillsEmphasizes visual storytelling via data visualizations.…

Condizione: As New. Unread book in perfect condition.

Condizione: New. In English.

Condizione: OTTIMO USATO. Da revisionare Francese Edizione autoprodotta in lingua francese, brossura artigianale con dedica estesa e firma al frontespizio. Lo stato interno à ottimo, pagine bianche perfettamente legate alla cerniera, tagli immacolati. Copertina di carta morbida, illustrata in cornice, leggera usura segna le punte, ma rimangono molto buone le condizioni conservative. Luogo d'edizione non specificato. N. pag. 285.…

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: New. Legal scholarship is one of the oldest academic disciplines, and the study of law has been passed on from generation to generation as an implicit "savoir faire". It was presumed that all legal scholars understood the methodology of legal research, making its explicit clarification and justification unnecessary. Over the last decade, the lack of an explicit methodological tradition has become problematic due to the growing interdisciplinary collaboration at universities and the increased importance of external funding, often granted by mixed experts panels. It is therefore time for legal scholarship to make its implicit methodology explicit.This handbook -created on the basis of a PhD project defended at KU Leuven Law Faculty in 2016 - carefully describes the methodology of traditional legal research in four sections:- First, the different types of research objectives that legal scholars can pursue are clarified.- Secondly, as each type of research objective calls for its own methodology, their methodological features are discussed individually.- Thirdly, after looking into each research objective separately, three overall methodological features applicable to all are addressed.- Fourthly, the theory of the previous parts is transformed into a practical methodological guide. This guide serves as a useful instrument for legal scholars who aim to design or reflect on research projects.…