Udemy – The Ultimate Beginner’s Guide to Genetic Algorithms in Python 2022-2 – Download

Description

The ultimate beginner’s guide to genetic algorithms in Python published by Udemy Academy. Implementing genetic algorithms from scratch to solve real-world problems!

Genetic algorithms are an important area of ​​artificial intelligence responsible for solving complex real-world problems. There are many practical applications of this type of algorithm that can be used to solve problems in everyday business situations. A classic example is solving the problem of scheduling teachers in schools, where there are different combinations of schedules and classes, and the goal is to build the schedule dynamically based on the number of classes and the availability of each teacher. Other examples are: telecommunications companies can design new optical networks, operators can better plan the delivery route of goods, investors can choose the best investment. Among several others

In this course you will learn everything you need to enter the world of genetic algorithms! What makes this course unique is that you will learn basic intuition and most importantly step-by-step implementation without using pre-built libraries. In other words, we will implement genetic algorithms from scratch using Python. If you have never heard of this subject, at the end of the course you will have all the theoretical and practical bases to solve your problems or the company you work for!

What you will learn in The Ultimate Beginner’s Guide to Genetic Algorithms in Python course:

  • Learn the basic concepts of genetic algorithms in theory and practice, such as: individual, population, crossover/production, mutation and evaluation.
  • Implementation of genetic algorithms from scratch in Python.
  • Use genetic algorithms to maximize and minimize problems.
  • Visualize the results of genetic algorithms using dynamic graphs.
  • Integration of genetic algorithms with the MySql database.
  • Learn how to create genetic algorithms using the DEAP and MLROSe libraries.
  • And…

Who should attend :

  • People interested in genetic algorithms, optimization algorithms or artificial intelligence
  • People interested in implementing genetic algorithms from scratch.
  • People interested in the DEAP and MLROSe libraries
  • Students studying subjects related to artificial intelligence.
  • Data scientists who want to deepen their knowledge of genetic algorithms.

Course Specifications

Course themes End of 2022/2

The Ultimate Beginner's Guide to Genetic Algorithms in Python

Course prerequisites

programming logic
Basic Python Programming

Pictures

The Ultimate Beginner's Guide to Genetic Algorithms in Python

Introductory Video for the Ultimate Beginner’s Guide to Genetic Algorithms in Python

installation guide

After the clip, watch with your favorite reader.

english subtitles

Quality: 720p

Download link

Download Part 1 – 1 GB

Download part 2 – 658 MB

password file(s): free download software

File size

1.65 GB

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