312 - What are genetic algorithms?

Genetic Algorithms (GA) are a type of evolutionary algorithm inspired by the process of natural selection in biological evolution.​

They can be used to solve optimization problems, including finding the optimal values for various parameters.​

GAs involve creating a population of candidate solutions, which are then evolved through the application of selection, crossover, and mutation operators.​

The fittest individuals from each generation are selected to create the next generation, creating a process of natural selection over multiple generations.​

GAs involve the application of selection, crossover, and mutation operators to create the next generation of individuals.​

The selection operator involves selecting the fittest individuals from the current generation to create the next generation.​

The crossover operator involves combining the genetic material of two individuals to create a new individual.​

The mutation operator involves randomly changing the genetic material of an individual to introduce new variations in the population.​

​GAs have been successfully applied to various optimization problems, including finding the optimal values for various parameters in machine learning models.​

They have also been used for feature selection, where the algorithm selects the best set of features for a particular task.​

Other applications of GAs include optimization of engineering designs, scheduling problems, and financial forecasting.​

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[saranshgautam]

So happy that you're covering Genetic Algorithms!!

[andreipotra]

Hey DigitalSreeni, i just wanted to tell you that i really appreciate your kind person and your hard work, you inspired me in being curious, wish you the best.

[Brickkzz]

Can't wait for the Python video. I want to use this to analyse electronci health records

[smoothumut]

After seeing and watching your videos on youtube for years, I have finally decided to subscribe. Great and basic explanation of the genetic algorithm. Easy to understand and digest. looking forward for the implementation. Thank you very much

[Khaled_Elsadani]

Thanks for the great effort, waiting for the coming videos.

[palurikrishnaveni]

Thanks for making this video, eagerly waiting for the implementation part, and can you do videos on various optimization algorithms like bayesian, butterfly algorithms etc.,
Yours videos are very helpful for my research work. Thank you so much, sir.

[vimalshrivastava]

I have learnt a lot from your semantic segmentation videos. If you get time, please make videos on semantic segmentation using a transformer. Thanks in advance...!!!

[sw]

Great explanation, can't wait for your upcoming DIY examples ❤

[srivathsansanthanam]

Hey sreeni, I would love to see a video on Feature selection for classification or semantic segmentation using GA....

[babakmemar]

Thank you so much, wonderful like always 🙏🏻🙏🏻

[J.M.MALHOTRAASSOCIATES]

Is crossover mandatory or after making selection using tournament selection. We can specify either the selected are chosen for crossover or randomly chose one of them for mutation
If anyone can guide

[dantec.dagandanan]

sir, can you do an example using nato-technology. thank you