- Machine Learning
- Applied Mathematics
- Data Preprocessing
- NumPy
- Machine Learning Methods
- Algebra
- Python Programming
- Dimensionality Reduction
- Data Manipulation
- Mathematical Modeling
- Advanced Mathematics
- Linear Algebra
Linear Algebra for Machine Learning and Data Science
Completed by EKO RACHMAT SATRIYO
September 18, 2023
34 hours (approximately)
EKO RACHMAT SATRIYO's account is verified. Coursera certifies their successful completion of Linear Algebra for Machine Learning and Data Science
What you will learn
Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence
Apply common vector and matrix algebra operations like dot product, inverse, and determinants
Express certain types of matrix operations as linear transformation, and apply concepts of eigenvalues and eigenvectors to machine learning problems
Skills you will gain
