Written in easy to read language, and packed with practical, easily applied tips, this eBook contains everything you need to know to take great notes.To make sure you get the most value for money possible I've also included the FREE eBook: "How to Study: 20 Tips". It contains my best best advice on time management, goal setting and how to get the best grades with the least effort. It's advice that also transfers brilliantly well to professionals, the self employed and anyone working toward mastery of a given field.

    He likes singing and watching TV in the family room. There are also things that Tom enjoys doing in private, like touching his penis.This accessible and positive resource helps parents and carers teach boys with autism or other special needs about masturbation. It covers when and where it is appropriate and helps to establish boundaries surrounding privacy more generally. With simple but explicit illustrations, this book provides the perfect platform to talk about sexuality with boys and young men with autism or special needs.

    Includes chapters on orbital mechanics, spacecraft construction, satellite-path radio wave propagation, modulation techniques, multiple access, and a detailed analysis of the communications link.

    As the size and complexity of commercial software have grown, the gap between academic computer science and industry has widened. It's an open secret that there is little engineering in software engineering, which continues to rely not on codified scientific knowledge but on intuition and experience.Barr, who worked as a programmer for more than twenty years, describes how the industry has evolved, from the era of mainframes and Fortran to today's embrace of the cloud. He explains bugs and why software has so many of them, and why today's interconnected computers offer fertile ground for viruses and worms. The difference between good and bad software can be a single line of code, and Barr includes code to illustrate the consequences of seemingly inconsequential choices by programmers. Looking to the future, Barr writes that the best prospect for improving software engineering is the move to the cloud. When software is a service and not a product, companies will have more incentive to make it good rather than "good enough to ship."

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

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    It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    It illustrates both the cohesiveness of the relatively few fundamental ideas in this area and the great variety of problems these ideas solve. All of the problems address principles and procedures inherent in the design and anlysis of engineering structures and mechanical systems, with many of the problems referring explicitly to design considerations.

    The layout of the book covers the following: Laplace transforms, mathematical model

    Aimed at electrical and computing engineerering and undergraduates in computer architecture. Third revised edition.

    It includes three entirely new chapters on the Internet, computer graphics, and multimedia. Thorough yet flexible, Introduction to Computers is appropriate for a full-semester course -- with or without a hands-on lab. The text is available with a student CD-ROM that contains interactive multimedia materials for each chapter. Also available are an Electronic Study Guide on CD-ROM, HyperGraphics package, and an Instructor's Productivity Center on CD-ROM.

    This is the autobiography of Bhyrappa who lost his mother at the age of eleven, both sister and brother with plague on the same day when he was nine. At the age of fourteen; he had to carry the dead body of his younger brother to cremate. He was looked after by an uncle who used physically punish him and an aunt who was cruel to him. He begged for food, walked 600 miles to Bombay with the dream of making his life. Working as a hotel waiter, assistant in a theatre company. . At last he managed to continue education, completed Ph.D., and grew as novelist. This autobiography. In every sense factual, reads like a novel and has become a model of autobiography writing.

    KEY TOPICS: Coverage begins with an optional review of key concepts--such as properties of compound semiconductor, quantum mechanics, semiconductor statistics, carrier transport properties, optical processes, and junction theory--then progress gradually through more advanced topics. The Second Edition has been both updated and expanded to include the recent developments in the field.

    It describes the theory with examples step by step. It contains the description of writing tehse steps in programs in very easy and understanble manner.