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1. |
Record Nr. |
UNISALENTO991000863019707536 |
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Autore |
Ortese, Anna Maria |
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Titolo |
Il cardillo addolorato / Anna Maria Ortese |
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ISBN |
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Descrizione fisica |
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Collana |
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Disciplina |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910827499203321 |
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Autore |
Miller James D. |
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Titolo |
Mastering predictive analytics with R : machine learning techniques for advanced models / / James D. Miller, Rui Miguel Forte |
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Pubbl/distr/stampa |
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Birmingham : , : Packt, , 2017 |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (449 pages) : illustrations |
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Soggetti |
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R (Computer program language) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Sommario/riassunto |
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Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a |
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range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do y... |
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3. |
Record Nr. |
UNINA9910513577503321 |
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Autore |
Ghosh Bimal |
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Titolo |
The 2018 Global Migration Compact : A Major Breakthrough or an Opportunity Lost or Both? / / by Bimal Ghosh |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Palgrave Macmillan, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (97 pages) |
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Disciplina |
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Soggetti |
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Labor economics |
International economic relations |
Law and economics |
Labor Economics |
International Economics |
Law and Economics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1. Why a multilateral agreement on migration is so important and yet why so difficult to achieve it -- 2. How valid are these constraints -- 3. Attempts at reaching a multilateral agreement on migration: a synoptic history -- 4. The New York Declaration and the 2018 Global Compact on Migration -- 5. What makes the Compact incomplete and lopsided -- 6. Conclusions. |
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Sommario/riassunto |
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This book analyses the 2018 Global Compact on Migration and the need for, and difficulties of adopting a multilateral agreement on migration. Particular attention is given to the challenges and constraints involved, given not only the divergent needs and conditions of different counties but also the varying interests of different groups within countries. A synoptic history of previous attempts at reaching a multilateral migration agreement is provided, from 1927 onwards, to give context to the recent negotiations. [The lack of a clear recognition of migration as a global process and the absence of a firm commitment |
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to responsibility- sharing arrangements are highlighted.] [The book explains why the 2018 migration is both a breakthrough and at the same time an opportunity lost. In doing so,] it also analyses the limitations of the present deal, including inadequate attention to the root causes of forced and disruptive migration in origin countries, and highlights how the 2018 agreement can be built upon to create a dynamic harmony in the global migration system. The book will be relevant to researchers and policy makers as well as to professionals and activists concerned with migration, labour economics and international development. |
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