{"product_id":"date-science-books-2-in-1-essential-math-data-science-practical-statistics","title":"Data Science Books 2-in-1 deal (Essential Math Data Science + Practical Statistics)","description":"\u003cp data-start=\"0\" data-end=\"354\"\u003e\u003cspan\u003e\u003cspan style=\"font-size: large;\"\u003eEssential Math for Data Science by Thomas Nield\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"0\" data-end=\"354\"\u003e\u003cspan style=\"font-size: large;\"\u003eBuild a strong foundation in data science with\u003cspan\u003e \u003c\/span\u003e\u003cem data-start=\"131\" data-end=\"164\" data-is-only-node=\"\"\u003eEssential Math for Data Science\u003c\/em\u003e\u003cspan\u003e \u003c\/span\u003eby Thomas Nield. This practical guide introduces the core mathematical concepts needed to understand and work with data effectively, including linear algebra, probability, and statistics.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"356\" data-end=\"670\"\u003e\u003cspan style=\"font-size: large;\"\u003eNield breaks down complex ideas into clear, intuitive explanations, helping readers grasp how mathematical principles apply to real-world data analysis and machine learning. With examples and problem-solving approaches, the book supports learners in developing both conceptual understanding and practical skills.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"672\" data-end=\"830\" data-is-last-node=\"\" data-is-only-node=\"\"\u003e\u003cspan style=\"font-size: large;\"\u003eAccessible and focused, this edition is ideal for beginners and aspiring data scientists looking to take control of data through essential mathematical tools.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"672\" data-end=\"830\" data-is-last-node=\"\" data-is-only-node=\"\"\u003e\u003cspan style=\"font-size: large;\"\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"672\" data-end=\"830\" data-is-last-node=\"\" data-is-only-node=\"\"\u003e\u003cspan\u003e\u003cspan style=\"font-size: large;\"\u003ePractical Statistics for Data Scientists 50+ Essential Concepts Using R \u0026amp; Pyt\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-start=\"672\" data-end=\"830\" data-is-last-node=\"\" data-is-only-node=\"\"\u003e\u003cspan style=\"font-size: large;\"\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan style=\"font-size: large;\"\u003eStatistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan style=\"font-size: large;\"\u003eMany data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you'll learn: \u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eWhy exploratory data analysis is a key preliminary step in data science \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eHow random sampling can reduce bias and yield a higher-quality dataset, even with big data \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eHow the principles of experimental design yield definitive answers to questions \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eHow to use regression to estimate outcomes and detect anomalies \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eKey classification techniques for predicting which categories a record belongs to \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eStatistical machine learning methods that \"learn\" from data \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"font-size: large;\"\u003eUnsupervised learning methods for extracting meaning from unlabeled data\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Pearl Press","offers":[{"title":"Default Title","offer_id":46215641170117,"sku":"810326826","price":57.95,"currency_code":"AUD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0685\/7660\/8453\/files\/s-l1600_575116e9-5676-4dd8-a1d4-8244eb118535.webp?v=1779001136","url":"https:\/\/pearlpress.com.au\/products\/date-science-books-2-in-1-essential-math-data-science-practical-statistics","provider":"Pearl Press","version":"1.0","type":"link"}