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paperback. Zustand: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Sprache: Englisch
Verlag: O'Reilly Media (edition 1), 2022
ISBN 10: 1098102932 ISBN 13: 9781098102937
Anbieter: BooksRun, Philadelphia, PA, USA
Paperback. Zustand: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Zustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Anbieter: CollegePoint, Inc, Jamestown, TN, USA
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Paperback. Zustand: Good. 1st Edition. We only honor returns for quality issues and won't accept reasons such as 'change my mind', 'find a better price', or 'school book requirement change', etc.
Zustand: Used - Very Good. Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career.Learn how to: Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance Manipulate vectors and matrices and perform matrix decomposition Integrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networks Navigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market.
Zustand: New.
Paperback or Softback. Zustand: New. Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics. Book.
Anbieter: Lakeside Books, Benton Harbor, MI, USA
Zustand: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Zustand: New.
Zustand: As New. Unread book in perfect condition.
Zustand: New.
EUR 42,49
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Paperback. Zustand: New. To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus.Practical examples with Python code will help you see how the math applies to the work you'll be doing, providing a clear understanding of how concepts work under the hood while connecting them to applications like machine learning. You'll get a solid foundation in the math essential for data science, but more importantly, you'll be able to use it to:Recognize the nuances and pitfalls of probability mathMaster statistics and hypothesis testing (and avoid common pitfalls)Discover practical applications of probability, statistics, calculus, and machine learningIntuitively understand linear algebra as a transformation of space, not just grids of numbers being multiplied and addedPerform calculus derivatives and integrals completely from scratch in PythonApply what you've learned to machine learning, including linear regression, logistic regression, and neural networks.
Verlag: O'Reilly Media
Anbieter: Academic Book Solutions, Medford, NY, USA
paperback. Zustand: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
Sprache: Englisch
Verlag: O'Reilly Media, Sebastopol, 2022
ISBN 10: 1098102932 ISBN 13: 9781098102937
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: new. Paperback. To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus.Practical examples with Python code will help you see how the math applies to the work you'll be doing, providing a clear understanding of how concepts work under the hood while connecting them to applications like machine learning. You'll get a solid foundation in the math essential for data science, but more importantly, you'll be able to use it to:Recognize the nuances and pitfalls of probability mathMaster statistics and hypothesis testing (and avoid common pitfalls)Discover practical applications of probability, statistics, calculus, and machine learningIntuitively understand linear algebra as a transformation of space, not just grids of numbers being multiplied and addedPerform calculus derivatives and integrals completely from scratch in PythonApply what you've learned to machine learning, including linear regression, logistic regression, and neural networks To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 54,14
Anzahl: Mehr als 20 verfügbar
In den WarenkorbPaperback. Zustand: New. To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus.Practical examples with Python code will help you see how the math applies to the work you'll be doing, providing a clear understanding of how concepts work under the hood while connecting them to applications like machine learning. You'll get a solid foundation in the math essential for data science, but more importantly, you'll be able to use it to:Recognize the nuances and pitfalls of probability mathMaster statistics and hypothesis testing (and avoid common pitfalls)Discover practical applications of probability, statistics, calculus, and machine learningIntuitively understand linear algebra as a transformation of space, not just grids of numbers being multiplied and addedPerform calculus derivatives and integrals completely from scratch in PythonApply what you've learned to machine learning, including linear regression, logistic regression, and neural networks.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 42,47
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In den WarenkorbZustand: New.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 49,02
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In den WarenkorbZustand: New. In.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 56,82
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In den WarenkorbZustand: New.
Sprache: Englisch
Verlag: O'Reilly Media 2022-06-10, 2022
ISBN 10: 1098102932 ISBN 13: 9781098102937
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
EUR 46,58
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In den WarenkorbPaperback. Zustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 47,24
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In den WarenkorbZustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Zustand: new.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 50,39
Anzahl: 2 verfügbar
In den WarenkorbZustand: As New. Unread book in perfect condition.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 64,70
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. 350 pages. 9.19x7.00x0.73 inches. In Stock.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New.
Zustand: New. 2022. Paperback. . . . . .
Zustand: New. 1st edition NO-PA16APR2015-KAP.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career. 333 pp. Englisch.
Anbieter: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career. 333 pp. Englisch.