{"product_id":"data-science-analytics-and-machine-learning-with-r-paperback-9780128242711","title":"Data Science, Analytics and Machine Learning with R (Paperback) 9780128242711","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eData Science, Analytics and Machine Learning with R\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eOffers a practical R-based toolkit for data analysis using different machine learning techniques\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eLuiz Paulo Favero (Author), Patricia Belfiore (Author), Rafael de Freitas Souza (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780128242711, Elsevier Science\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePaperback, published 25 January 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e660 pages, 400 illustrations (200 in full color)\u003cbr\u003e27.6 x 21.6 x 4 cm, 1.77 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003ci\u003eData Science, Analytics and Machine Learning with R\u003c\/i\u003e explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning.\u003c\/p\u003e  \u003cp\u003eIn addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cb\u003ePart I: Introduction\u003c\/b\u003e\u003cbr\u003e1. Overview of Data Science, Analytics, and Machine Learning\u003cbr\u003e2. Introduction to the R Language\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart II: Applied Statistics and Data Visualization\u003c\/b\u003e\u003cbr\u003e3. Variables and Measurement Scales\u003cbr\u003e4. Descriptive and Probabilistic Statistics\u003cbr\u003e5. Hypotheses Tests\u003cbr\u003e6. Data Visualization and Multivariate Graphs\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart III: Data Mining and Preparation\u003c\/b\u003e\u003cbr\u003e7. Building Handcrafted Robots\u003cbr\u003e8. Using APIs to Collect Data\u003cbr\u003e9. Managing Data\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart IV: Unsupervised Machine Learning Techniques\u003c\/b\u003e\u003cbr\u003e10. Cluster Analysis\u003cbr\u003e11. Factorial and Principal Component Analysis (PCA)\u003cbr\u003e12. Association Rules and Correspondence Analysis\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart V: Supervised Machine Learning Techniques\u003c\/b\u003e\u003cbr\u003e13. Simple and Multiple Regression Analysis\u003cbr\u003e14. Binary, Ordinal and Multinomial Regression Analysis\u003cbr\u003e15. Count-Data and Zero-Inflated Regression Analysis\u003cbr\u003e16. Generalized Linear Mixed Models\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart VI: Improving Performance and Introduction to Deep Learning\u003c\/b\u003e\u003cbr\u003e17. Support Vector Machine\u003cbr\u003e18. CART (Classification and Regression Trees)\u003cbr\u003e19. Bagging, Boosting and Uplift (Persuasion) Modeling\u003cbr\u003e20. Random Forest\u003cbr\u003e21. Artificial Neural Network\u003cbr\u003e22. Introduction to Deep Learning\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart VII: Spatial Analysis\u003c\/b\u003e\u003cbr\u003e23. Working on Shapefiles\u003cbr\u003e24. Dealing with Simple Features Objects\u003cbr\u003e25. Raster Objects\u003cbr\u003e26. Exploratory Spatial Analysis\u003cbr\u003e\u003cbr\u003e\u003cb\u003ePart VII: Adding Value to your Work\u003c\/b\u003e\u003cbr\u003e27. Enhanced and Interactive Graphs\u003cbr\u003e28. Dashboards with R\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Machine learning [\u003ca title=\"See our other books on Machine learning\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Machine%20learning%20%5BUYQM%5D%22\"\u003eUYQM\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Academic Press","offers":[{"title":"Default Title","offer_id":46648080072984,"sku":"9780128242711","price":88.45,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/products\/9780128242711.jpg?v=1694088133","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/data-science-analytics-and-machine-learning-with-r-paperback-9780128242711","provider":"Freshly Printed Books","version":"1.0","type":"link"}