Essential Math for Data Science

Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics

Author: Thomas Nield

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9789355422743
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    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
    Books
    Author
    Thomas Nield
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Lead time to ship in days (if not in stock)
    ships in 12-15 days
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    352
    Publication Date
    28/05/2022
    Publisher
    Shroff/O'Reilly
    Year
    2022
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.65 inch

    Table of Contents (9789355422743_toc.pdf, 40 Kb) [Download]

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