List of Top Mathematical & Statistical Software Books by US Book Publishers

Here is a list of top mathematical and statistical software books published by US book publishers:

1. "R for Data Science" by Hadley Wickham and Garrett Grolemund

2. "Python for Data Science Handbook" by Jake VanderPlas

3. "An Introduction to Statistical Learning" by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

4. "The Art of Data Science" by Roger D. Peng

5. "Data Science from Scratch" by Joel Grus

6. "Doing Data Science" by Cathy O'Neil and Rachel Schutt

7. "Data Science for Business" by Foster Provost and Tom Fawcett

8. "Introduction to Statistical Thinking (With R, Without Calculus)" by Ben Lambert

9. "Applied Multivariate Statistical Analysis" by Richard Johnson and Dean Wichern

10. "Introduction to Data Mining" by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar

These books cover a range of topics in mathematical and statistical software, including data visualization, machine learning, and statistical modeling. They are aimed at a variety of audiences, from beginners to advanced practitioners, and are written by leading experts in the field.

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