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First published in 1997. This volume discusses the notion of whether there is a limit to knowledge and 'One Way to Know', in addition to the suggestion that that we no longer need to know, and whether our continued employment of knowing (cognition, epistemology) is useful or useless and destructive of human life and development.
Start With Why has led millions of readers to rethink everything they do – in their personal lives, their careers and their organizations. Now Find Your Why picks up where Start With Why left off. It shows you how to apply Simon Sinek’s powerful insights so that you can find more inspiration at work -- and in turn inspire those around you. I believe fulfillment is a right and not a privilege. We are all entitled to wake up in the morning inspired to go to work, feel safe when we’re there and return home fulfilled at the end of the day. Achieving that fulfillment starts with understanding exactly WHY we do what we do. As Start With Why has spread around the world, countless readers have asked me the same question: How can I apply Start With Why to my career, team, company or nonprofit? Along with two of my colleagues, Peter Docker and David Mead, I created this hands-on, step-by-step guide to help you find your WHY. With detailed exercises, illustrations, and action steps for every stage of the process, Find Your Why can help you address many important concerns, including: * What if my WHY sounds just like my competitor’s? * Can I have more than one WHY? * If my work doesn’t match my WHY, what should I do? * What if my team can’t agree on our WHY? Whether you've just started your first job, are leading a team, or are CEO of your own company, the exercises in this book will help guide you on a path to long-term success and fulfillment, for both you and your colleagues. Thank you for joining us as we work together to build a world in which more people start with WHY. Inspire on! -- Simon
In 'Unconscious Knowing and Other Essays in Psycho-Philosophical Analysis', Linda Brakel tackles a range of fascinating and puzzling phenomena that lie at the border between psychoanalysis and philosophy of mind. These include - unconscious knowing, vagueness, agency, the placebo effect, and even explanation itself. Unique in its use of tools and concepts from both philosophy and psychoanalysis, the book demonstrates how this interdisciplinary approach can provide some unique solutions to some impenetrable problems. Following the introduction, chapter two on 'unconscious knowing' puts forward a radical epistemological view of knowledge and belief, providing evidence from psychoanalytic data and empirical research, using the subliminal method. Chapter three considers philosophical accounts of vagueness in relation to a-rational mentation, finding surprising similarities. In Chapter four, an original account of agency is developed whilst discovering that a central problem for analysands is quite analogous to an important philosophical problem: namely, when I am concerned with my own survival, just what is the nature of the 'me' of concern? In Chapter five the mysterious placebo effect is made more understandable in terms of the basic psychoanalytic concepts that are shown to underlie it. Finally, chapter six concludes the book with an examination of explanations in general, including those in the proceeding chapters. This is a book that will be of great interest to those within both psychoanalysis and philosophy of mind, offering up some compelling explanations for some puzzling phenomena.
A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition of a comprehensive, widely used machine learning textbook offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neural networks. The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing. The fourth edition offers a new chapter on deep learning that discusses training, regularizing, and structuring deep neural networks such as convolutional and generative adversarial networks; new material in the chapter on reinforcement learning that covers the use of deep networks, the policy gradient methods, and deep reinforcement learning; new material in the chapter on multilayer perceptrons on autoencoders and the word2vec network; and discussion of a popular method of dimensionality reduction, t-SNE. New appendixes offer background material on linear algebra and optimization. End-of-chapter exercises help readers to apply concepts learned. Introduction to Machine Learning can be used in courses for advanced undergraduate and graduate students and as a reference for professionals.
This book is intended to provide engineering and/or statistics students, communications engineers, and mathematicians with the firm theoretic basis of source coding (or data compression) in information theory. Although information theory consists of two main areas, source coding and channel coding, the authors choose here to focus only on source coding. The reason is that, in a sense, it is more basic than channel coding, and also because of recent achievements in source coding and compression. An important feature of the book is that whenever possible, the authors describe universal coding methods, i.e., the methods that can be used without prior knowledge of the statistical properties of the data. The authors approach the subject of source coding from the very basics to the top frontiers in an intuitively transparent, but mathematically sound, manner. The book serves as a theoretical reference for communication professionals and statisticians specializing in information theory. It will also serve as an excellent introductory text for advanced-level and graduate students taking elementary or advanced courses in telecommunications, electrical engineering, statistics, mathematics, and computer science.
This essential companion to Chaitins highly successful The Limits of Mathematics, gives a brilliant historical survey of important work on the foundations of mathematics. The Unknowable is a very readable introduction to Chaitins ideas, and includes software (on the authors website) that will enable users to interact with the authors proofs. "Chaitins new book, The Unknowable, is a welcome addition to his oeuvre. In it he manages to bring his amazingly seminal insights to the attention of a much larger audience His work has deserved such treatment for a long time." JOHN ALLEN PAULOS, AUTHOR OF ONCE UPON A NUMBER
The main objective of this session is to present these Christian Characters, otherwise known as virtues, in a way that will compel the students to apply them to their own lives. Using a building theme will help you dissect each characteristic and make every nuance count. The Lord is never finished working on us in this life, we are all in a building program, trying to becom more like Jesus. Share this with your students! Let them know that they are not alone in facing the growing pains of life! The more colorful and creative that you get with your lesson, the greater the possibility that the students will listen, be involved and allow themselves to be molded and changed. Dive into these featured characteristics and gain a deeper understanding and appreciation of each of their qualities. Listed below are definitions and such to help you present each character in a more complete form. Loyalty, Confidence, Integrity, Self-Control, Patience, Compassion, Wisdom and Courage.
Structural Acoustics and Vibration presents the modeling of vibrations of complex structures coupled with acoustic fluids in the low and medium frequency ranges. It is devoted to mechanical models, variationalformulations and discretization for calculating linear vibrations in the frequency domain of complex structures. The book includes theoretical formulations which are directly applicable to develop computer codes for the numerical simulation of complex systems, and gives a general scientific strategy to solve various complex structural acoustics problems in different areas such as spacecraft, aircraft, automobiles, and naval structures. The researcher may directly apply the material of the book to practical problems such as acoustic pollution, the comfort of passengers, and acoustic loads induced by propellers. Structural Acoustics and Vibration considers the mechanical and numerical aspects of the problem, and gives original solutions to the predictability of vibrations of complex structures interacting with internal and external, liquid and gaseous fluids. It is a self-contained general synthesis with a didactic presentation and fills the gap between analytical methods applied to simple geometries and statistical methods, which are useful in high frequency structural acoustic problems. Provides for the first time complex structures in scientific literature Presents a self-contained general synthesis with a didactic presentation Integrates the most advanced research topics on the subject Enables the researcher to solve complex structural acoustics problems in areas such as spacecraft, aircraft, automobiles, and naval structures Fills the gap between analytical methods applied to simple geometries and statistical methods Contains advanced mechanical and numerical modeling Provides appropriate formulations directly applicable for developing computer codes for the numerical simulation of complex systemssystems
This classic book covers the solution of differential equations in science and engineering in such as way as to provide an introduction for novices before progressing toward increasingly more difficult problems. The Method of Weighted Residuals and Variational Principles describes variational principles, including how to find them and how to use them to construct error bounds and create stationary principles. The book also illustrates how to use simple methods to find approximate solutions, shows how to use the finite element method for more complex problems, and provides detailed information on error bounds. Problem sets make this book ideal for self-study or as a course text.