More than two centuries after Euler's death, it is still regarded as a conceptual diamond of unsurpassed beauty. Called Euler's identity or God's equation, it includes just five numbers but represents an astonishing revelation of hidden connections. It ties together everything from basic arithmetic to compound interest, the circumference of a circle, trigonometry, calculus, and even infinity. In David Stipp's hands, Euler's identity formula becomes a contemplative stroll through the glories of mathematics. The result is an ode to this magical field.

    

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    It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

    The author has sought to utlilize the technology now available for the teaching and learning of calculus. The hand-held graphics calculator is one such form of technology that has been integrated into the book. Topics in algebra, trigonometry, and analytical geometry appear in the Appendix.

    Like its predecessors, the seventh edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the book an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how book principles work in professional practice. Includes easy-to-understand explanations of difficult statistical topics, such as sampling distributions, relationship between confidence level and confidence interval, interpreting r-square. A complete package of teaching/learning aids is provided in every chapter, including chapter review exercises, chapter concepts tests,"Statistics at Work" conceptual cases, "Computer Database Exercises," "From the Textbook to the Real-World Examples." This ISBN is in two volumes Part A and Part B.

    It allows one to gain information by discarding information, namely, the individuality of the observations. Stigler s second pillar, information measurement, challenges the importance of big data by noting that observations are not all equally important: the amount of information in a data set is often proportional to only the square root of the number of observations, not the absolute number. The third idea is likelihood, the calibration of inferences with the use of probability. Intercomparison is the principle that statistical comparisons do not need to be made with respect to an external standard. The fifth pillar is regression, both a paradox (tall parents on average produce shorter children; tall children on average have shorter parents) and the basis of inference, including Bayesian inference and causal reasoning. The sixth concept captures the importance of experimental design for example, by recognizing the gains to be had from a combinatorial approach with rigorous randomization. The seventh idea is the residual the notion that a complicated phenomenon can be simplified by subtracting the effect of known causes, leaving a residual phenomenon that can be explained more easily.The Seven Pillars of Statistical Wisdom presents an original, unified account of statistical science that will fascinate the interested layperson and engage the professional statistician."

    Every complete program uses a consistent style, and as programs are analyzed, styles and standards are further explained. Whenever possible, the authors develop the principle of a subject before they introduce the language implementation so the student understands the concept before dealing with the nuances of C++. In addition, a vast array of figures and tables visually reinforce key concepts. By integrating software engineering principles and encouraging the student to resist the temptation to immediately code, the text builds a solid foundation in problem solving.

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    Yet as bestselling author and astrophysicist Jeffrey Bennett points out, black holes don't suck. With that simple idea in hand, Bennett begins an entertaining introduction to Einstein's theories, describing the amazing phenomena readers would actually experience if they took a trip through a black hole.The theory of relativity also gives us the cosmic speed limit of the speed of light, the mind-bending ideas of time dilation and curvature of spacetime, and what may be the most famous equation in history: e = mc2. Indeed, the theory of relativity shapes much of our modern understanding of the universe, and it is not "just a theory: " every major prediction of relativity has been tested to exquisite precision and its practical applications include the Global Positioning System (GPS). Bennett proves anyone can understand the basics of Einstein's ideas. His intuitive, nonmathematical approach gives a wide audience its first real taste of how relativity works and why it is so important not only to science but also to the way we view ourselves as human beings.

    Then, attempting to break a Nazi code during World War II, he successfully designed and built one, thus ensuring the Allied victory. Turing became a champion of artificial intelligence, but his work was cut short. As an openly gay man at a time when homosexuality was illegal in England, he was convicted and forced to undergo a humiliating "treatment" that may have led to his suicide.With a novelist's sensitivity, David Leavitt portrays Turing in all his humanity—his eccentricities, his brilliance, his fatal candor—and elegantly explains his work and its implications.

    It is ideal for students preparing to take the state civil service examinations or any other competitive exams where Indian history is a subject of relevance.The first section begins by looking at the pre-historic cultures in India and goes on to discuss the Indus valley civilization and the Mauryan empire. The second section, on medieval India, looks at significant developments post Gupta dynasty and the rise and fall of the Mughal empire. The third section is on modern India, which majorly focuses on the advent of British rule in the country and the Indian struggle for independence.Each section in the book begins with a brief overview of the period represented through a chronological timeline. A separate section on revision is given at the end, followed by a series of model test papers for self-evaluation.About Krishna ReddyKrishna Reddy has also authored Bharat Ka Itihas and General Knowledge Digest 2010.

    It covers all the major cutting-edge technologies of production automation and material handling, and how these technologies are used to construct modern manufacturing systems. Manufacturing Operations; Industrial Control Systems; Sensors, Actuators, and Other Control System Components; Numerical Control; Industrial Robotics; Discrete Control Using Programmable Logic Controllers and Personal Computers; Material Transport Systems; Storage Systems; Automatic Data Capture; Single Station Manufacturing Cells; Group Technology and Cellular Manufacturing; Flexible Manufacturing Systems; Manual Assembly Lines; Transfer Lines and Similar Automated Manufacturing Systems; Automated Assembly Systems; Statistical Process Control; Inspection Principles and Practices; Inspection Technologies; Product Design and CAD/CAM in the Production System; Process Planning and Concurrent Engineering; Production Planning and Control Systems; and Lean Production and Agile Manufacturing. For anyone interested in Automation, Production Systems, and Computer-Integrated Manufacturing.

    Explaining why the whole is sometimes smarter than the sum of its parts, Johnson presents surprising examples of feedback, self-organization, and adaptive learning. How does a lively neighborhood evolve out of a disconnected group of shopkeepers, bartenders, and real estate developers? How does a media event take on a life of its own? How will new software programs create an intelligent World Wide Web? In the coming years, the power of self-organization -- coupled with the connective technology of the Internet -- will usher in a revolution every bit as significant as the introduction of electricity. Provocative and engaging, Emergence puts you on the front lines of this exciting upheaval in science and thought.

    Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.