In this book we will be concerned with supervised learning, which is the problem of learning input-output mappings from empirical data (the training dataset). Depending on the characteristics of the output, this problem is known as either regression, for continuous outputs, or classification, when outputs are discrete.
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Haskell is a deep language, and learning it is a hugely rewarding experience. In this ebook, you’ll approach programming from a different and valuable perspective. You’ll also learn how to create software that is short, fast, and safe. Lastly, you’ll have the pleasure of applying beautiful programming techniques to solve real problems.
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This book provides hands-on introduction to the collection and analysis of Twitter data from the perspective of a novice. No knowledge of data analysis, or social network analysis is presumed. For all the concepts discussed in this book, we will provide in-depth description of the underlying assumptions and explain via construction of examples.
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A book to give beginning computer science majors a solid foundation for further study. It is also to give students who will not take advanced courses in computer science the conceptual tools that the field provides.
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The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical text on Bayesian inference involves two to three chapters on probability theory, then enters what Bayesian inference is.
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This book is the bare minimum guide helping you to start programming from scratch. In almost anything, the hardest part is to get the ball rolling. After reading this book you will be comfortable with programming.
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A guide to using the libsodium PHP extension for modern, secure, and fast cryptography. Developers can now develop fast, secure, and reliable applications without needing to know what a stream cipher even is.
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The idea of this series came to the author’s mind after European Common Lisp Meeting 2011 where he had had a chance to meet in person some of those mythical 100x more productive programmers.
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