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As part of its BMW H2R research project, Studio Olafur Eliasson presents extensive visual material; excerpts from two seminars held in 2006/07; and conversations between designers and theorists. Finally, the 'climate car' consists of a car with a surface of layers of ice which has to be at -6 degrees Celsius.
As more users expect to use their mobile devices, librarians will want and need to develop the necessary skills to reach this growing user base. Mobile Devices: A Practical Guide for Librarians will aid libraries and librarians as they go through the process of planning, developing, implementing, marketing, and evaluating mobile services. Based on research and experience using and developing for mobile devices, this guides includes information and ideas regarding: Why mobile technologies are important for libraries Developing mobile websites and applications for specific mobile platforms such as iOS and Android using existing web technologies such as HTML, CSS, and Javascript Using mobile devices for reference, library instruction, and shelf reading Marketing strategies to make users aware of mobile services Evaluating mobile services A must-read for librarians interested in mobile technologies and services, this guide with provide librarians with practical information and examples to develop and offer mobile services in their libraries.
How does a CEO, manager, or entrepreneur begin to sort out what defines and drives a good customer experience and how it can be measured and made actionable? If you know how well the customer experience is satisfying your customers and you know how to increase their satisfaction, you can then increase sales, return visits, recommendations, loyalty, and brand engagement across all channels. More reliable and more useful data leads to better decisions and better results. Innovating Analytics is also about the need for a comprehensive measurement ecosystem to accurately assess and improve the other elements of customer experience. This is a time of great change and great opportunity. The companies that use the right tools and make the right assessments of how to satisfy their customers will have the competitive advantage. Innovating Analytics introduces an index that measures a customer’s likelihood to recommend and the likelihood to detract. The current concept of the Net Promoter Score (NPS) that has been adopted by many companies during the last decade—is no longer accurate, precise or actionable. This new metric called the Word of Mouth Index (WoMI) has been tested on hundreds of companies and with over 1.5 million consumers over the last two years. Author Larry Freed details the improvement that WoMI provides within what he calls the Measurement Ecosystem. He then goes on to look at three other drivers of customer satisfaction along with word of mouth: customer acquisition, customer loyalty, and customer conversion.
Dig deep into the data with a hands-on guide to machine learning with updated examples and more! Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: Learn the languages of machine learning including Hadoop, Mahout, and Weka Understand decision trees, Bayesian networks, and artificial neural networks Implement Association Rule, Real Time, and Batch learning Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.