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Abstract
The objective of this tool is to summarize and illustrate the common mathematical concepts from Calculus to Linear Algebra in Python 3 Jupyter Notebook.
The tool includes practical applications and example problems for students to practice the concepts they have acquired through the interactive modules.
TABLE OF CONTENTS:
Calculus
- Derivatives
- Single Integrals
- Series
Statistics
- Probability Density
- Uniform Random Distribution
- Gaussian Distribution
In Development
- Series (Update date: TBA)
- Taylor Series (Release date: TBA)
- Multiple Integrals (Release date: TBA)
- Partial Derivatives (Release date: TBA)
- Vectors and Gradient (Release date: TBA)
- Divergence (Release date: TBA)
- Curl (Release date: TBA)
- Eigenvectors and Eigenvalues (Release date: TBA)
References
Stewart, J. (2016) Calculus. 8th ed. Boston: Cengage Learning
Thomas, G. B., Weir, M. D., Hass, J. R. (2010) Thomas' Calculus: Early Transcendentals. 12th ed. Boston: Pearson
Yougn, H. D., Freedman, R. A., Ford, A. L. (2016) University Physics with Modern Physics. 14th ed. Pearson
Beer, F. P., Johnston, E. R. Jr., Mazurek, D. F., Cornwell, P. J., Self, B. P. (2016) Vector Mechanics for Engineers: Statics and Dynamics. 11th ed. New York: McGraw-Hill Education
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