<p>This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments.</p><p>To this end, the book is divided into three parts, each focusing on a different area. Part I begins by introducing how basic numerical techniques are performed in OCaml, including classical mathematical topics (interpolation and quadrature), statistics, and linear algebra. It moves on from using only scalar values to multi-dimensional arrays, introducing the tensor and Ndarray, core data types in any numerical computing system. It concludes with two more classical numerical computing topics, the solution of
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Building upon the wide-ranging success of the first edition, Parallel Scientific Computation presents a single unified approach to using a range of parallel computers, from a small desktop computer to a massively parallel computer. The author explains...
kr 569.00
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<b>A stunning collection of the best in Chinese Science Fiction, from Award-Winning legends to up-and-coming talent, all translated here into English for the first time. </b><BR><BR>This celebration of Chinese Science Fiction...
kr 169.00
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This book will appeal to undergraduate students of geography and related disciplines with a regional focus on China and to the general reader who wants to learn different geographical aspects of modern China with little academic background in geography.
kr 719.00
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