"Mathematics consists of proving the most obvious thing in the least obvious way" - Raleigh N C
Different people have different perceptions of math. For some, its a bliss while for some it's dreadful. Well, don't worry. We have got your back even if you hated math during your school days. The best thing about data science is that you can actually see the math getting applied right in front of you. This real-time application-based approach makes math more captivating to learn as a data scientist.
Here is a quick comprehensive list that might help you!
Linear Algebra
1. Vectors
2. Matrices
3. Transpose of a matrix
4. Inverse of a matrix
5. Determinant of a matrix
6. Trace of a matrix
7. Dot product
8. Eigenvalues
9. Eigenvectors
10. Single Value Decomposition
Differential Calculus
1. Chain Rule Of Differentiation
2. Partial Derivatives
3. Integrations
4. Beta and gamma functions
5. Functions Of Multiple Variable, Limit, continuity, partial derivatives
6. Variants Of Optimizers
7. Loss Functions
8. Back Propagation
9. Minima And Maxima
Image Courtesy: http://www.nexiats.com.sg/wp-content/uploads/2017/11/Nexia-Pulse-Q3-2017.pdf
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