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[null,"1.","Record Nr.",null,"UNINA9910461859103321"]
[null,null,"Titolo",null,"Gaming, governance and public policy in Macao [[electronic resource] /] / edited by Newman M. K. Lam and Ian Scott"]
[null,null,"Pubbl/distr/stampa",null,"Hong Kong, : Hong Kong University Press"]
[{"$nulls":4},"Macau, : University of Macau, c2011"]
[null,null,"ISBN",null,"988-220-982-3"]
[{"$nulls":4},"988-8053-82-5"]
[null,null,"Descrizione fisica",null,"1 online resource (319 p.)"]
[null,null,"Disciplina",null,"351.5"]
[null,null,"Soggetti",null,"Gambling industry - China - Macau (Special Administrative Region)"]
[{"$nulls":4},"Gambling industry - Government policy - China - Macau (Special Administrative Region)"]
[{"$nulls":4},"Gambling industry - Social aspects - China - Macau (Special Administrative Region)"]
[{"$nulls":4},"Gambling industry - Economic aspects - China - Macau (Special Administrative Region)"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [269]-281) and index."]
[null,null,"Nota di contenuto",null,"1. Social stability and economic growth / Ian Scott -- pt. 1. The gaming industry and its critics -- 2. The development of the gaming industry and its impact on land use / Penny Wan and Francisco V. Pinheiro -- 3. The impact of gaming liberalisation on public opinion and political culture / Newman M.K. Lam -- pt. II. Governance -- 4. Executive-legislative relationships and the development of public policy / Eilo Yu Wing Yat -- 5. Challenges and threats to traditional associations / Annie Lee Shuk Ping -- 6. Civil service reform : building basic administrative capacity / Brian Brewer -- 7. Improving productivity through efficiency wages : the case of the civil service / Jeannette Taylor -- pt. III. Public policy -- 8. Labour policy : resolving the mismatch between demand and supply / Grace O.M. Lee -- 9. Labour regulation in the liberalised casino economy : the case of the croupiers / Alex H. Choi and Eva P.W. Hung -- 10. Education governance and reform : bringing the state back in / Joan Y.H. Leung -- 11. Housing policy : a neoliberal agenda? / James Lee -- 12. Social welfare policy : a \"flexible\" strategy? / Chan Kam Wah and James Lee -- pt. Iv. "]
[{"$nulls":4},"Conclusions -- 13. Gaming, governance and public policy : constraints and opportunities / Ian Scott and Newman M.K. Lam -- Appendix : timeline Macao 1999-2010 -- Notes and references -- Selected bibliography -- Index."]
[null,null,null,"Sommario/riassunto","Macao has undergone a remarkable transformation since the liberalisation of the gaming industry in 2002. In this book, scholars examine the effects of massive foreign investment, the problems of governance and the increasing public policy challenges in the context of rapid change and potential social instability."]
[null,"2.","Record Nr.",null,"UNINA9910825995703321"]
[null,null,"Autore",null,"Fandango Armando"]
[null,null,"Titolo",null,"Mastering TensorFlow 1.x : advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras / / Armando Fandango"]
[null,null,"Pubbl/distr/stampa",null,"Birmingham, England : , : Packt Publishing, , 2018"]
[{"$nulls":4},"2018"]
[null,null,"Edizione",null,"[1st edition]"]
[null,null,"Descrizione fisica",null,"1 online resource (474 pages)"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Machine learning - Mathematical models"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,null,"Sommario/riassunto","Build, scale, and deploy deep neural network models using the star libraries in Python About This Book Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras Build, deploy, and scale end-to-end deep neural network models in a production environment Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow Scale and deploy production models with distributed and high-performance computing on GPU and clusters Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and "]
[{"$nulls":4},"Android devices Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow ..."]