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Essential Math for Data Science by Thomas Nield
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Essential Math for Data Science by Thomas Nield
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.You might also like
Thomas Nield is the founder of Nield Consulting Group as well as an instructor at O'Reilly Media and University of Southern California. He enjoys making technical content relatable and relevant to those unfamiliar or intimidated by it. Thomas regularly teaches classes on data analysis, machine learning, mathematical optimization, and practical artificial intelligence. He's authored two books, including Getting Started with SQL (O'Reilly) and Learning RxJava (Packt).
| SKU | Unavailable |
| ISBN 13 | 9781098102937 |
| ISBN 10 | 1098102932 |
| Title | Essential Math for Data Science |
| Author | Thomas Nield |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | O'Reilly Media |
| Year published | 2022-06-10 |
| Number of pages | 350 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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