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Essential Math for Data Science - Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics (Paperback)
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Essential Math for Data Science - Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics (Paperback)
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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 math Master statistics and
hypothesis testing (and avoid common pitfalls) Discover practical
applications of probability, statistics, calculus, and machine
learning Intuitively understand linear algebra as a transformation
of space, not just grids of numbers being multiplied and added
Perform calculus derivatives and integrals completely from scratch
in Python Apply what you've learned to machine learning, including
linear regression, logistic regression, and neural networks
General
| Imprint: |
O'Reilly Media
|
| Country of origin: |
United States |
| Release date: |
June 2022 |
| Authors: |
Thomas Nield
|
| Dimensions: |
177 x 232 x 22mm (L x W x T) |
| Format: |
Paperback
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| Pages: |
350 |
| ISBN-13: |
978-1-09-810293-7 |
| Categories: |
Books
Promotions
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| LSN: |
1-09-810293-2 |
| Barcode: |
9781098102937 |
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