With this concise book, you will quickly gain working knowledge of Sinatra and its minimalist approach to building both standalone and modular web applications. Sinatra serves as a lightweight wrapper around Rack middleware, with syntax that maps closely to functions exposed by HTTP verbs, which makes it ideal for web services and APIs. If you have experience building applications with Ruby, you’ll quickly learn language fundamentals and see under-the-hood techniques, with the help of several practical examples. Then you’ll get hands-on experience with Sinatra by building your own blog engine. Learn Sinatra’s core concepts, and get started by building a simple application Create views, manage sessions, and work with Sinatra route definitions Become familiar with the language’s internals, and take a closer look at Rack Use different subclass methods for building flexible and robust architectures Put Sinatra to work: build a blog that takes advantage of service hooks provided by the GitHub API

    HELP, I'M FALLING APART!!This quick read is informative and entertaining, with personal stories and documented research.

    Thus CHACHA CHAUDHARY was born in 1971.Tall and robust SABU, who is an inhabitant of planet Jupiter, gave Chaudhary an ideal company. A combination of wisdom and strength was formed to tackle any difficult task. It is said that " Chacha Chaudhary's brain works faster than a computer". Though both fight the criminals and tricksters, each episode ends with a touch of humour. The duo perform in lighter vein. The CHAUDHARY family consists of his wife Bini, a fat sharp tongue woman, Sabu, Rocket - the dog and Dag- Dag, an old truck who is half human- half machine. Chacha Chaudhary is the most popular Indian comics. More than 10 million readers enjoy this series regularly in newspapers and comic books in ten languages. A T.V. serial based on the comics has crossed 500 episodes and still continue to be telecast on premier channel "Sahara ONE".

    Deputy Marshal in Kansas for a great deal of his life. As soon as his brother Tommy stops answering his letters, he gets extremely alarmed and decides to take matters into his own hands. When he puts a plan in place to travel to Texas, little does he know that a shattering surprise awaits him there; his brother has been found dead, next to the body of one of the most powerful ranchers in town. Will Lee manage to unravel the truth behind these enigmatic and shocking deaths?While Lee is still aghast, the local sheriff declares Tommy's death a suicide, and also accuses him of attempting robbery and murder. On the spur of the moment, the case is considered closed, which makes Lee highly suspicious. Feeling that they drag Tommy's name through the mud, he decides to defy the law and seek vindication. Will he succeed in this lonesome yet risky mission? How will he solve this demanding riddle and clear his brother's name?Lee's hazardous quest begins, having Susan Marsh and Ki'Somma, a young Cherokee medicine man, on his side. Doubts, lies, deceits, serious injuries as well as many other roadblocks will derange their endless undertaking. Will they manage to join forces triumphantly and complete this challenging mission? Or will Tommy always be remembered as a ruthless criminal?

    She is always on the trail of atrocious criminals but when her ruse is almost uncovered, her world turns upside down and she is desperate to find someone to pull her out of the fire. Luckily for her, she will partner up with Willem Stron, a lionhearted man and passing gambler who will pose as Kyle. Together they will join forces on a risky mission to guard a passing stagecoach with precious cargo. When their lives are on the line, will Willem eventually win Daisy's trust, so that they both succeed on this highly challenging undertaking?While Daisy and Willem are planning the perilous ambush, a deep affection grows for one another. Day by day, their lifetime adventure brings them closer, but they both know that if they want to stay on course, they will need to set their happily ever after aside. While struggling to focus on their quest, the sudden appearance of a wanted poster with Willem's face causes yet another series of menacing threats. How will Daisy and Willem react to this unexpected turn of events? Will they ever escape from this living nightmare and have a chance at love?When the stagecoach becomes targeted by a vicious local bandit and his gang, the two bounty hunters will deal with endless challenges that block their way. Will the legendary duo manage to protect the secretive cargo, and live to tell the tale? Or will the forces of corruption and greed overtake them at long last?A pulse-pounding drama, which will make you turn the pages with bated breath until the very last word. A must-read for fans of Western action and romance.

    His books have been read by over 1,000,000 people and are #1 best-sellers. His book Beginning Ubuntu Linux recently entered its sixth edition, and picked-up a Linux Journal award along the way. Thomas is also the author of Ubuntu Kung Fu. * * * * * * * * * * * * * * * * * Get to grips with the Ubuntu command-line with this #1 best-selling and concise guide. "Best buck I've spent yet" — Amazon review.* Readable, accessible and easy to understand;* Learn essential Ubuntu vocational skills, or read just for fun;* Covers Ubuntu commands, syntax, the filesystem, plus advanced techniques;* For ANY version of Linux based on Debian, such as Linux Mint--not just Ubuntu!;* Includes BONUS introduction to Ubuntu chapter, plus a glossary appendix and a guide to reading Linux/Unix documentation.

    The calls to ban it were more or less instant.Re:cyclists is the tale of what happened next, of how we have spent two centuries wheeling our way about town and country on bikes--or on two-wheeled things that vaguely resembled what we now call bikes. Michael Hutchinson picks his way through those 200 years, discovering how cycling became a kinky vaudeville act for Parisians, how it became an American business empire, and how it went on to find a unique home in the British Isles. He considers the penny-farthing riders exploring the abandoned and lonely coaching roads during the railway era, and the Victorian high-society cyclists of the 1890s bicycle craze--a time when no aristocratic house party was without bicycles and when the Prince of Wales used to give himself an illicit thrill on a weekday afternoon by watching the women's riding-school in the Royal Albert Hall.Re:cyclists looks at how cycling became the sport, the pastime and the social life of millions of ordinary people, how it grew and how it suffered through the 1960s and '70s, and how at the dawn of the twenty-first century it rose again, much changed but still ultimately just someone careering along on two wheels.

     Solve the 100-year-old mystery which the great physicist, Paul Dirac, believed linked atoms to the secret of the entire universe.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."

    Her people have fled. And Mitch Ayers is having a real bad day. Fifty years ago, our home was dying. We identified worlds that might be able to support human life. We built Ark Ships: huge colonization vessels carrying thousands of crew. And we set out, not knowing if we could make it to the other side of the blackness, or whether there would be anything there if we did. Mitch wasn't supposed to have to care about any of this. He was supposed to be happily dreaming in stasis for another twenty years. That's until he wakes up on the Ark Ship Nansen, three light years off course, staring right up at the barrel of a gun. All around him, he hears the screams of the dying. Terrorists are wiping out the Nansen's crew while they sleep, and he's the only one who can do a damn thing about it. But ain't that always the way. Mitch knows the Nansen's crew might be the only humans left in the universe. The problem is, he quickly learns that humans aren't alone in the stars. Aliens aren't just out there, they're everywhere. And the first one he meets tries to sink its teeth into his neck... Mitch is a long way from home, and it's not just the aliens he's up against. It's the traitors within his own crew. Now humanity's fate rests on his shoulders. So he'll have to think fast...

    

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data