Gradient descent methods

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In this section, we will go through a particular class of problems where functions are differentiable.

This topic is often referred to as Non-Linear Programming, in contrast with Linear Programming which we will study in a further section.

	Topics
2.1	Example problems and modelling
2.2	A walk through gradient methods (notebook)
2.3	Solve the city placement problem (notebook)

Notebook sessions can be run on:

• your own computer: there are no specific requirements besides the numpy, matplotlib and scipy libraries.

• the computer in the classroom. Activate the environment before running Jupyter lab:

  # The following commands only work in the classroom
  module load python/3.7
  source activate ~x.olive/students
  

• Google Colab is a good fallback option, but data files must be uploaded, and solutions to exercices must be checked separately from the Github folder.