{"product_id":"data-science-in-r-a-case-studies-approach-to-computational-reasoning-and-problem-solving-9781138469297","title":"Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving","description":"\u003cp\u003e • Author(s): Deborah Nolan\u003cbr\u003e • Publisher: Taylor \u0026amp; Francis\u003cbr\u003e • Publisher Imprint: CRC Press\u003cbr\u003e • BISAC: Statistics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eEffectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation \u003cbr\u003eData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. \u003c\/p\u003e \u003cp\u003eThe book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: \u003c\/p\u003e \u003cp\u003eNon-standard, complex data formats, such as robot logs and email messages \u003cbr\u003eText processing and regular expressions \u003cbr\u003eNewer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth \u003cbr\u003eStatistical methods, such as classification trees, k-nearest neighbors, and na Bayes \u003cbr\u003eVisualization and exploratory data analysis \u003cbr\u003eRelational databases and Structured Query Language (SQL) \u003cbr\u003eSimulation \u003cbr\u003eAlgorithm implementation \u003cbr\u003eLarge data and efficiency\u003c\/p\u003e \u003cp\u003eSuitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.\u003c\/p\u003e \u003cp\u003eBlending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers computational reasoning of real-world data analyses.\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Hardcover","offer_id":45238660497559,"sku":"9781138469297","price":16757.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781138469297.webp?v=1769220392","url":"https:\/\/atlanticbooks.com\/products\/data-science-in-r-a-case-studies-approach-to-computational-reasoning-and-problem-solving-9781138469297","provider":"Atlantic Books","version":"1.0","type":"link"}