Think Stats is an introduction to Probability and Statistics for Python programmers. It emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health.
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The book is designed to appeal to students with only a modest mathematical background in undergraduate calculus and linear algebra. No formal computer science or statistical background is required to follow the book, although a basic familiarity with probability, calculus and linear algebra would be useful.
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This book will be useful for those in the scientific community who gather data and seek tools for analyzing and interpreting data. It will be a valuable reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis as well as a supplemental text in courses on research methodology, pattern recognition, image processing, and re-mote sensing.
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Digital Signal Processing is the science of using computers to understand these types of data. This includes a wide variety of goals: filtering, speech recognition, image enhancement, data compression, neural networks, and much more. DSP is one of the most powerful technologies that will shape science and engineering in the twenty-first century.
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This document is an introduction to ML programming, specifically for the Objective Caml (OCaml) programming language from INRIA. OCaml is a dialect of the ML (Meta-Language) family of languages, which derive from the Classic ML language designed by Robin Milner in 1975 for the LCF (Logic of Computable Functions) theorem prover.
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The goal of this paper is to describe how different software design and architectural patterns are applied in AngularJS or any AngularJS single-page application.
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If Dave Hewlett and Bill Packard, two Stanford graduates with the rosiest of futures ahead of them, can flounder so badly when faced with the problem of how to price their products, what hope do the rest of us have? Quite a lot, as it turns out.
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This ebook fills a useful need in explaining a new view of signal processing based on flexible time frequency analysis and its applications. It has been well received and used by researchers and engineers alike. In addition, it was also used as a textbook for graduate courses at several leading universities.
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