Useful Links
Computer Science
Data Science
NumPy Library
1. Introduction to NumPy
2. The NumPy ndarray Object
3. Data Types in NumPy
4. Array Creation Techniques
5. Indexing and Slicing
6. Array Manipulation and Reshaping
7. Universal Functions (ufuncs)
8. Array Aggregation and Statistics
9. Broadcasting
10. Linear Algebra Operations
11. Random Number Generation
12. File Input and Output
13. Advanced NumPy Features
14. NumPy Ecosystem Integration
15. Best Practices and Common Pitfalls
Linear Algebra Operations
Basic Linear Algebra
Matrix Multiplication
dot()
matmul()
@ Operator
Vector Operations
inner()
outer()
cross()
vdot()
Matrix Properties
trace()
diagonal()
Advanced Linear Algebra (numpy.linalg)
Matrix Decompositions
cholesky()
qr()
svd()
lu()
Eigenvalue Problems
eig()
eigh()
eigvals()
eigvalsh()
Matrix Analysis
det()
slogdet()
matrix_rank()
cond()
Norms
norm()
Vector Norms
Matrix Norms
Solving Linear Systems
solve()
lstsq()
tensorsolve()
Matrix Inversion
inv()
pinv()
tensorinv()
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11. Random Number Generation