Reshmi R Nair Free Video Download
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Circular Economy and Re-Commerce in the Fashion Industry
The apparel industry has the scale, reach, and technical expertise to deliver on-target sustainable development goals within the industry’s sphere of influence in its interconnected global and local value chains. From the farm to the consumer, the textile, retail, and apparel production industry has an array of economic, environmental, social, and governance impacts. In order to meet sustainable goals, the industry is challenged to buy and produce goods and services that do not harm the environment, society, and the economy. Circular Economy and Re-Commerce in the Fashion Industry is a pivotal reference source that explores and proposes solutions for best practices to meet sustainable development goals in the fashion industry and provides guidelines for assessing the technological landscape and modeling sustainable business practices. Highlighting a wide range of topics including digital marking, consumer behavior, and social and legal perspectives, this book is ideally designed for suppliers, brand managers, retailers, multinational investors, marketers, executives, designers, manufacturers, policymakers, researchers, academicians, and students.
Deep Learning
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Doing Business 2017
Author: World Bank
language: en
Publisher: World Bank Publications
Release Date: 2016-10-25
Fourteenth in a series of annual reports comparing business regulation in 190 economies, Doing Business 2017 measures aspects of regulation affecting 10 areas of everyday business activity: • Starting a business • Dealing with construction permits • Getting electricity • Registering property • Getting credit • Protecting minority investors • Paying taxes • Trading across borders • Enforcing contracts • Resolving insolvency These areas are included in the distance to frontier score and ease of doing business ranking. Doing Business also measures features of labor market regulation, which is not included in these two measures. This year’s report introduces major improvements by expanding the paying taxes indicators to cover postfiling processes—tax audits, tax refunds and tax appeals—and presents analysis of pilot data on selling to the government which measures public procurement regulations. Also for the first time this year Doing Business collects data on Somalia, bringing the total number of economies covered to 190. Using the data originally developed by Women, Business and the Law, this year for the first time Doing Business adds a gender component to three indicators—starting a business, registering property, and enforcing contracts—and finds that those economies which limit women’s access in these areas have fewer women working in the private sector both as employers and employees. The report updates all indicators as of June 1, 2016, ranks economies on their overall “ease of doing business†?, and analyzes reforms to business regulation †“ identifying which economies are strengthening their business environment the most. Doing Business illustrates how reforms in business regulations are being used to analyze economic outcomes for domestic entrepreneurs and for the wider economy. It is a flagship product produced in partnership by the World Bank Group that garners worldwide attention on regulatory barriers to entrepreneurship. More than 137 economies have used the Doing Business indicators to shape reform agendas and monitor improvements on the ground. In addition, the Doing Business data has generated over 2,182 articles in peer-reviewed academic journals since its inception.