Called a madman by his enemies, a genius by others, and an enigma by nearly everyone, Nikola Tesla was, without a doubt, a trailblazing inventor who created astonishing, sometimes world-transforming devices that were virtually without theoretical precedent. Tesla not only discovered the rotating magnetic field -- the basis of most alternating-current machinery -- but also introduced us to the fundamentals of robotics, computers, and missile science. Almost supernaturally gifted, unfailingly flamboyant and neurotic, Tesla was troubled by an array of compulsions and phobias and was fond of extravagant, visionary experimentations. He was also a popular man-about-town, admired by men as diverse as Mark Twain and George Westinghouse, and adored by scores of society beauties. From Tesla's childhood in Yugoslavia to his death in New York in the 1940s, Cheney paints a compelling human portrait and chronicles a lifetime of discoveries that radically altered -- and continue to alter -- the world in which we live. Tesla: Man Out of Time is an in-depth look at the seminal accomplishments of a scientific wizard and a thoughtful examination of the obsessions and eccentricities of the man behind the science.

    It provides many detailed, practical design and analysis examples intended to relate theory to the workplace. Chapter topics include first experiences with an op amp; inverting and noninverting amplifiers; comparators and controls; selected applications of op amps; signal generators; op amps with diodes; differential, instrumentation, and bridge amplifiers; DC performance: bias, offsets, and drift; AC performance: bandwidth, slew rate, noise; active filters; modulating, demodulating, and frequency changing with the multiplier; integrated-circuit timers; digital-to-analog converters; analog-to-digital converters; and power supplies. For design engineers rs

    In this unconventional introduction, physicist Leonard Susskind and hacker-scientist George Hrabovsky offer a first course in physics and associated math for the ardent amateur. Unlike most popular physics books—which give readers a taste of what physicists know but shy away from equations or math—Susskind and Hrabovsky actually teach the skills you need to do physics, beginning with classical mechanics, yourself. Based on Susskind's enormously popular Stanford University-based (and YouTube-featured) continuing-education course, the authors cover the minimum—the theoretical minimum of the title—that readers need to master to study more advanced topics.An alternative to the conventional go-to-college method, The Theoretical Minimum provides a tool kit for amateur scientists to learn physics at their own pace.

     If you have ever found yourself lost halfway through other introductory materials on this topic, this is the book for you. If you don't understand set terminology such as vectors, hyperplanes, and centroids, then this is also the book for you. This starter course isn't a picture story book but does include many visual examples that break algorithms down into a digestible and practical format. As a starter course, this book connects the dots and offers the crash course I wish I had when I first started. The kind of guide I wish had before I started taking on introductory courses that presume you’re two days away from an advanced mathematics exam. That’s why this introductory course doesn’t go further on the subject than other introductory books, but rather, goes a step back. A half-step back in order to help everyone make his or her first strides in machine learning and is an ideal study companion for the visual learner. In this step-by-step guide you will learn: - How to download free datasets - What tools and software packages you need - Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data - Preparing data for analysis, including k-fold Validation - Regression analysis to create trend lines - Clustering, including k-means and k-nearest Neighbors - Naive Bayes Classifier to predict new classes - Anomaly detection and SVM algorithms to combat anomalies and outliers - The basics of Neural Networks - Bias/Variance to improve your machine learning model - Decision Trees to decode classification Please feel welcome to join this starter course by buying a copy, or sending a free sample to your preferred device.

    Catapulted into the spotlight by witnessing a death on the baseball field, Thompson takes on the ‘ole boy club in this fast paced mystery of professional sports and political intrigue. Award winning author, Rick Robinson, hits a home run with his second novel. His first novel, The Maximum Contribution, was named Finalist for Best Political Fiction in the 2008 Next Generation Indie Book Awards. Robinson fans won’t be disappointed with this sequel!

    She begins to rebuild her life by focusing on a career. She is hired by Sharma Industries to avert the company’s collapse. Aditya, heir to Sharma Industries returns to India from the United States and moves right into Kirthi’s lonely and depressed heart, offering her a life she only dreamed about. Constrained by the oppressive taboo preventing all widows from remarrying, Kirthi struggles with the haunting question: would Aditya love her if he knew? Brought together by work, drawn closer through friendship, pulled apart by cultural taboos, their love shatters prejudice and offers hope.