The task is to learn different optimization algorithms such as gradient descent, newton-raphson methods that helps to minimize (maximize) given functions.
The problem is solved by creating functions that find the root of the function based on, namely 1) bisection method, 2) newton-raphson method, 3) gradient descent method. In addition, a function is written that optimizes given function based on inequality constraints.
There is no need for an explicit installation. However, the code can be executed using "python my_convex_optimization.py" command.
The functions inside of the project can be directly copied into required python notebooks, or they can be imported using import commands.
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