
Metaheuristics
Particle Swarm Optimization in MATLAB
Implement particle swarm optimization in MATLAB with velocity updates, bounds, inertia damping, constriction coefficients, and a Sphere test problem.


Metaheuristics
Implement particle swarm optimization in MATLAB with velocity updates, bounds, inertia damping, constriction coefficients, and a Sphere test problem.

Multiobjective Optimization
Implement NSGA-II in MATLAB with non-dominated sorting, crowding distance, genetic operators, and two-objective test problems.

Multiobjective Optimization
Run multi-objective PSO in MATLAB with an external repository, grid-based leader selection, mutation, and a two-objective test problem.

Courses
Implement bisection, a bracketed secant update and Newton-Raphson in Python and MATLAB. Compare assumptions, stopping criteria and two worked equations.

Metaheuristics
Build binary and real-coded genetic algorithms in MATLAB and Python, with seven videos on selection, crossover, mutation, bounds, and implementation.

Courses
Learn PCA in Python and MATLAB, from covariance and eigenvectors to projection, reconstruction, explained variance, and worked iris and digits examples.

Courses
A guided MATLAB course covering equations, matrices, interpolation, integration, polynomials, differential equations and optimization, with links to all seven chapters.

Courses
Model linear, integer, quadratic and nonlinear optimization problems in MATLAB. Follow worked examples and check feasibility, solver termination and local solutions.

Courses
Solve initial value, boundary value and delay differential equations in MATLAB. Follow oscillator examples and check tolerances, boundary conditions and history functions.

Courses
Work with MATLAB coefficient vectors to evaluate, fit, multiply, divide, differentiate and integrate polynomials. Check roots and division remainders.

Courses
Compute integrals and derivatives in MATLAB using functions or sampled data. Explore quadrature, trapezoidal integration, gradients, tolerances and sample spacing.

Courses
Compare polynomial fitting, grid interpolation, Fourier interpolation, splines and scattered-data methods in MATLAB, with practical checks for noisy data and extrapolation.

Courses
Learn eigenvalues, eigenvectors and SVD in MATLAB, including diagonalization, low rank image approximation and checks on the reconstructed matrices.

Courses
Solve polynomial, nonlinear and linear equations in MATLAB with roots, fzero, fsolve and linsolve. Compare the worked examples and learn how to check residuals.

Courses
Fit linear-in-parameter models in MATLAB, Python and JavaScript. Learn intercepts, feature matrices, pseudoinverses, rank conditions and practical checks on prediction error.

Courses
Solve linear difference equations using characteristic roots, initial conditions and particular solutions. Follow Fibonacci and repeated-root examples and verify each formula.

Courses
Build an RK4 solver in Python and MATLAB, simulate a predator-prey model and compare step sizes to understand accuracy and the limits of a fixed-step method.

Courses
Build linear programming models in MATLAB with linprog. Follow a worked maximization and a transportation model, then check constraints, bounds and variable ordering.

Metaheuristics
Define an optimization problem once in MATLAB and solve it with 15 algorithms through YPEA, with shared variable types, settings, and result histories.

Metaheuristics
Run particle swarm optimization in Python with NumPy, a reusable problem dictionary, configurable parameters, and a bounded Sphere example.

Multiobjective Optimization
Explore NSGA-III in MATLAB with reference points, objective normalization, association, niching, and a configurable optimization example.

Metaheuristics
Learn PSO in three videos, from the update equations to a MATLAB implementation with position bounds, velocity limits, and constriction coefficients.

Machine Learning
Extract supervised linear features in MATLAB with Fisher LDA, within- and between-class scatter, a generalized eigenproblem, and the iris dataset.

Metaheuristics
Implement a Cultural Algorithm in MATLAB with shared situational and normative knowledge, Gaussian moves, and a bounded Sphere example.

Metaheuristics
Apply simulated annealing to continuous variables in MATLAB, with Gaussian neighbors, bound handling, cooling, and a Sphere test problem.

Applications
Reduce image colors in MATLAB with k-Means, fuzzy c-Means, or a self-organizing map, using RGB or weighted HSV values and a smaller palette.

Applications
Study graph encoding in MATLAB with PSO, ICA, and Firefly search for a minimum spanning tree, and compare the result with an exact baseline.