This is the code developed to complete Georgia Tech CS 7641 (Machine Learning) assignment 2 (Randomized Optimization).

The objective was to test four random search approaches:

• Random Hill Climbing
• Simulated Annealing
• Genetic Algorithm
• MIMIC

Using four problems:

• Training the weights of a neural network
• OneMax
• Knapsack
• Four Peaks

The code is broken up into a Jupyter Notebook for each problem, with basic results described. Supporting helper functions are contained in utilities.py and utilities_hw2.py. Search algorithms are implemented in a modified version of the mlrose package, which is included in mlrose_local and must be intalled locally (pip -e ./mlrose_local)