This project showcases my skills in solving linear systems of equations using Gaussian Elimination and Row Echelon Form reduction. The code implements core algorithms for:
- Reading a matrix from a file.
- Performing row swaps, scaling rows, and adding/subtracting rows.
- Converting elements close to zero to zero for better readability.
- Transforming the matrix into Reduced Row Echelon Form (RREF).
- Identifying pivot variables and free variables.
- Constructing the solution vector in terms of pivot and free variables.
- Clear and concise code with meaningful variable names and comments.
- Modular functions for each operation, enhancing maintainability.
- Handles matrices with both square and non-square dimensions.
- Provides the solution in human-readable format, suitable for interpretation.
- Includes checks for zero pivots and handles empty solutions gracefully.
- Demonstrates understanding of fundamental linear algebra concepts.
- Highlights strong coding skills in Python, emphasizing clarity and efficiency.
- Showcases problem-solving ability and attention to detail.
- Solving systems of linear equations arising in various scientific and engineering domains.
- Analyzing data sets and extracting meaningful insights.
- Implementing machine learning algorithms that rely on linear algebra operations.
- Implement LU decomposition for more efficient solution in specific cases.
- Expand functionality to handle complex numbers.
- Integrate unit tests for robustness and correctness.