{"product_id":"essential-math-for-data-science","title":"Essential Math for Data Science:","description":"\u003ch4 data-section-id=\"da8d7w\" data-start=\"0\" data-end=\"21\"\u003eDetailed Overview:\u003c\/h4\u003e\n\u003cp data-start=\"25\" data-end=\"759\"\u003e\u003cstrong\u003e\u003cem data-start=\"25\" data-end=\"146\"\u003eEssential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics\u003c\/em\u003e by \u003cspan class=\"hover:entity-accent entity-underline inline cursor-pointer align-baseline\"\u003e\u003cspan class=\"whitespace-normal\"\u003eThomas Nield\u003c\/span\u003e\u003c\/span\u003e \u003c\/strong\u003eis a practical and beginner-friendly guide designed for aspiring data scientists, analysts, and machine learning enthusiasts who want to build a strong mathematical foundation without getting overwhelmed by complex theory. The book explains essential concepts such as algebra, calculus, probability, statistics, linear algebra, regression, and neural networks using clear language and real-world examples. Instead of focusing heavily on abstract equations, the author demonstrates how mathematical principles directly apply to data science and machine learning workflows.\u003c\/p\u003e\n\u003cp data-start=\"763\" data-end=\"1162\"\u003eReaders are introduced to key topics like descriptive statistics, probability distributions, matrices, gradient descent, logistic regression, and neural networks in an accessible and application-oriented manner. The book also incorporates Python examples using libraries such as NumPy, SymPy, and scikit-learn, making it ideal for practical learners who want hands-on understanding alongside theory.\u003c\/p\u003e\n\u003cp data-start=\"1166\" data-end=\"1675\"\u003eOne of the strongest aspects of this book is its ability to bridge the gap between mathematics and real-world data science applications. Thomas Nield’s engaging writing style makes complex concepts easier to understand for beginners while still offering valuable insights for intermediate learners. It is an excellent resource for students, self-taught programmers, data analysts, and professionals transitioning into artificial intelligence and machine learning careers\u003c\/p\u003e\n\u003cp data-start=\"1166\" data-end=\"1675\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0761\/2206\/3013\/files\/thoms_2.png?v=1779862537\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cdiv data-is-intersecting=\"true\" data-turn-id-container=\"3334d229-811a-49c5-9898-540dc2ad6d16\" class=\"\"\u003e\n\u003csection data-turn=\"user\" data-scroll-anchor=\"false\" data-testid=\"conversation-turn-9\" data-turn-id-container=\"3334d229-811a-49c5-9898-540dc2ad6d16\" data-turn-id=\"3334d229-811a-49c5-9898-540dc2ad6d16\" dir=\"auto\" class=\"text-token-text-primary w-full focus:outline-none has-data-writing-block:pointer-events-none [\u0026amp;:has([data-writing-block])\u0026gt;*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-(--header-height)\"\u003e\u003c\/section\u003e\n\u003cbr\u003e\n\u003c\/div\u003e\n\u003cdiv data-is-intersecting=\"true\" data-turn-id-container=\"request-WEB:a6c9a568-a8d0-430d-87b6-07fa1fc31f72-4\" class=\"\"\u003e\n\u003csection data-turn=\"assistant\" data-scroll-anchor=\"false\" data-testid=\"conversation-turn-10\" data-turn-id-container=\"request-WEB:a6c9a568-a8d0-430d-87b6-07fa1fc31f72-4\" data-turn-id=\"request-WEB:a6c9a568-a8d0-430d-87b6-07fa1fc31f72-4\" dir=\"auto\" class=\"text-token-text-primary w-full focus:outline-none has-data-writing-block:pointer-events-none [\u0026amp;:has([data-writing-block])\u0026gt;*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]\"\u003e\n\u003cdiv class=\"text-base my-auto mx-auto pb-10 [--thread-content-margin:var(--thread-content-margin-xs,calc(var(--spacing)*4))] @w-sm\/main:[--thread-content-margin:var(--thread-content-margin-sm,calc(var(--spacing)*6))] @w-lg\/main:[--thread-content-margin:var(--thread-content-margin-lg,calc(var(--spacing)*16))] px-(--thread-content-margin)\"\u003e\n\u003cdiv class=\"[--thread-content-max-width:40rem] @w-lg\/main:[--thread-content-max-width:48rem] mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\"\u003e\n\u003cdiv class=\"flex max-w-full flex-col gap-4 grow\"\u003e\n\u003cdiv data-turn-start-message=\"true\" class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal outline-none keyboard-focused:focus-ring [.text-message+\u0026amp;]:mt-1\" data-message-model-slug=\"gpt-5-5\" dir=\"auto\" data-message-id=\"062e1abc-7a7b-4bf3-8fe8-c8c2236d9271\" data-message-author-role=\"assistant\" tabindex=\"0\"\u003e\n\u003cdiv class=\"flex w-full flex-col gap-1 empty:hidden\"\u003e\n\u003cdiv class=\"markdown prose dark:prose-invert wrap-break-word w-full light markdown-new-styling\"\u003e\n\u003ch4 data-end=\"16\" data-start=\"0\"\u003e\u003cstrong\u003eProduct Details:\u003c\/strong\u003e\u003c\/h4\u003e\n\u003cp data-is-only-node=\"\" data-is-last-node=\"\" data-end=\"329\" data-start=\"18\"\u003e\u003cstrong\u003eTitle\u003c\/strong\u003e: Take Control of Your Data with Fundamental Linear Algebra, Probability\u003cbr data-end=\"146\" data-start=\"143\"\u003e\u003cstrong\u003eAuthor\u003c\/strong\u003e:Thomas Nield\u003cbr data-end=\"168\" data-start=\"165\"\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e:9781098102937\u003cbr data-end=\"192\" data-start=\"189\"\u003e\u003cstrong\u003eISBN-10:\u003c\/strong\u003e1098102932\u003cbr data-end=\"213\" data-start=\"210\"\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e:O'Reilly Media\u003cbr data-end=\"240\" data-start=\"237\"\u003e\u003cstrong\u003eBinding\u003c\/strong\u003e:Paperback\u003cbr data-end=\"260\" data-start=\"257\"\u003e\u003cstrong\u003eNo of Pages:\u003c\/strong\u003e349 Pages\u003cbr data-end=\"284\" data-start=\"281\"\u003e\u003cstrong\u003eLanguage\u003c\/strong\u003e:English\u003cbr data-end=\"303\" data-start=\"300\"\u003e\u003cstrong\u003ePublisher Date\u003c\/strong\u003e:5 July 2022\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c\/div\u003e","brand":"The Books Empire","offers":[{"title":"Default Title","offer_id":47858679906469,"sku":null,"price":32.9,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0761\/2206\/3013\/files\/thomas.jpg?v=1779862797","url":"https:\/\/thebooksempire.com\/products\/essential-math-for-data-science","provider":"The Books Empire","version":"1.0","type":"link"}