| 1 | Compute the Gram Matrix of a Set of Vectors | Easy | Linear Algebra |
| 2 | Compute the Symmetric Part of a Matrix | Easy | Linear Algebra |
| 3 | Extract the Diagonal Elements of a Matrix | Easy | Linear Algebra |
| 4 | Compute the Frobenius Norm of a Matrix | Easy | Linear Algebra |
| 5 | Hadamard Product of Two Matrices | Easy | Linear Algebra |
| 6 | Compute the Characteristic Polynomial Coefficients of a 2x2 Matrix | Medium | Linear Algebra |
| 7 | Compute Matrix Power | Medium | Linear Algebra |
| 8 | Compute the Adjugate of a 2x2 Matrix | Easy | Linear Algebra |
| 9 | Kronecker Product of Two Matrices | Medium | Linear Algebra |
| 10 | Compute the Pearson Correlation Matrix | Easy | Statistics |
| 11 | Solve Linear Equations Using the Gauss-Seidel Method | Medium | Linear Algebra |
| 12 | QR Decomposition of a 2x2 Matrix via Gram-Schmidt | Hard | Linear Algebra |
| 13 | LU Decomposition of a 3x3 Matrix | Hard | Linear Algebra |
| 14 | Logistic Regression Using Gradient Descent | Easy | Machine Learning |
| 15 | Polynomial Regression via Gradient Descent | Easy | Machine Learning |
| 16 | Robust Scaling Implementation | Easy | Machine Learning |
| 17 | Implement Fuzzy C-Means Clustering | Medium | Machine Learning |
| 18 | Implement Stratified K-Fold Cross-Validation | Medium | Machine Learning |
| 19 | Linear Discriminant Analysis (LDA) for Dimensionality Reduction | Medium | Machine Learning |
| 20 | Random Forest Classification from Scratch | Hard | Machine Learning |