Eric Ma – författare
343 kr
Kommande
2 325 kr
Skickas inom 10-15 vardagar
695 kr
Skickas inom 10-15 vardagar
824 kr
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The idea of ‘national identity’ is an ambiguous one for Hong Kong. Returned to the national embrace of China on 1 July 1997 after 150 years as a British colony, the concept of national identity and what it means to "belong to a nation" is a matter of great tension and contestation in Hong Kong.
Written by three academic specialists on Hong Kong cultural identity, social history, and mass media, this book explores the processes through which the people of Hong Kong are "learning to belong to a nation" by examining their relationship with the Chinese nation and state in the recent past, present, and future. It considers the complex meanings of and debates over national identity in Hong Kong over the past fifty years and especially during the last decade following Hong Kong’s return to China. It also places these arguments within a larger, global perspective, to ask what Hong Kong can teach us about national identity and its potential transformations.
Multidisciplinary in its approach, Hong Kong and China explores national identity in terms of theory, mass media, survey date, ethnography and history, and will appeal to students and scholars of Chinese history, cultural studies, and nationalism.
824 kr
Läs direkt efter köp
The idea of ‘national identity’ is an ambiguous one for Hong Kong. Returned to the national embrace of China on 1 July 1997 after 150 years as a British colony, the concept of national identity and what it means to "belong to a nation" is a matter of great tension and contestation in Hong Kong.
Written by three academic specialists on Hong Kong cultural identity, social history, and mass media, this book explores the processes through which the people of Hong Kong are "learning to belong to a nation" by examining their relationship with the Chinese nation and state in the recent past, present, and future. It considers the complex meanings of and debates over national identity in Hong Kong over the past fifty years and especially during the last decade following Hong Kong’s return to China. It also places these arguments within a larger, global perspective, to ask what Hong Kong can teach us about national identity and its potential transformations.
Multidisciplinary in its approach, Hong Kong and China explores national identity in terms of theory, mass media, survey date, ethnography and history, and will appeal to students and scholars of Chinese history, cultural studies, and nationalism.
154 kr
Skickas inom 5-8 vardagar
538 kr
Skickas
474 kr
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Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ
Key Features
A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.Book Description
The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models.
The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others.
By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to.
What you will learn
Build probabilistic models using the Python library PyMC3 Analyze probabilistic models with the help of ArviZ Acquire the skills required to sanity check models and modify them if necessary Understand the advantages and caveats of hierarchical modelsFind out how different models can be used to answer different data analysis questionsCompare models and choose between alternative onesDiscover how different models are unified from a probabilistic perspective Think probabilistically and benefit from the flexibility of the Bayesian frameworkWho this book is for
If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.