Learn to solve optimization problems in Python using essential math tools, metaheuristic methods, and constrained optimization techniques. Master efficient solutions for real-world applications.

Optimization with Python from zero to hero.png

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Optimization theory seeks the best solution, which is pivotal for machine learning, cost-cutting in manufacturing, refining logistics, and boosting finance profits.

This course provides a detailed description of different optimization problems and the techniques used to solve them. You’ll begin with the formal definition of an optimization problem and an overview of essential mathematical tools: derivatives, gradients, and Hessian. With this knowledge, you’ll implement solutions for several optimization problems. You’ll also learn approximate metaheuristic population methods like particle swarm optimization and genetic algorithms, and solve constrained optimization problems using techniques like penalty methods and constraint simplification. Finally, you’ll solve linear programs and integer programs. 

By the end of this course, you’ll become proficient in formulating different kinds of problems as optimization problems and become skilled in the Python tools that efficiently solve these problems.

Mastering Optimization with Python

# Installing Python on Linux

In Linux, Python is commonly installed by default. We can check if we've installed Python by running the following command in our preferred shell. 
```bash
python3 --version
``` 
If we get an error, then we need to install Python. But we can do it easily with the following command:

```bash
sudo apt-get python3
```

It requires elevated permission.

>**Note:** We'll be using version 3 of Python. Version 2 is deprecated and it isn't compatible with version 3. Make sure that the version of Python on your PC begins with a 3 (e.g., 3.10.4).

Those who're in **Linux** will also need to install ```pip```, the Python package manager. We'll need it to install the libraries we'll be using later. Install ```pip``` by running the following command:
```bash
sudo apt-get install python3-pip
```
Again, this requires elevated permission.

# Installing Python on iOS

On **iOS**, the process is very similar. We can install Python with the command.
```
brew install python3
```
We assume you have ```homebrew``` installed. To install ```pip```, we need to do three easy steps:

* Run the command:
```bash
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
```
It will download a file called get-pip.py. 

*  Execute the downloaded file running:

```bash
python3 get-pip.py
```

* Wait through the installation process.

# Installing Python on Windows

To install Python on Windows, we need to download an installer from the [official Python website](https://www.python.org). Select the installer that suits your operating system. Keep in mind it should be version 3 of Python (i.e., the version number must begin with 3).

Once we execute the file and go through the installation process, we'll have both Python and ```pip``` installed on Windows.

# Installing the libraries

The last thing to do is install the libraries we mentioned before. Fortunately, the way to do that is the same in all operating systems. We can install all of them with a single command.

```bash
pip3 install sympy matplotlib numpy scipy cvxopt cvxpy
```

>**Note:** In Windows, you may have just ```pip``` instead of ```pip3```, as well as ```python``` instead of ```python3```. Don't worry, if you followed the installation guidelines, you should have version 3 of Python and ```pip```. You can check it by running ```python --version``` and make sure that the version begins with 3.

The installation process could take a while. After the completion of the installation, we'll be all set.

Go through the installation process step by step.

Introduction

Derivatives and Gradients

First Optimization Algorithms

Population Methods

Adding Constraints

Solving Sudoku and the 8-Queens Puzzle as Constraint Satisfaction

Linear Constrained Optimization

Summary and Conclusion

Appendix

Maze Solver Using the Ant Colony Optimization Algorithm

Tools Installation