Genetic Algorithms in Python - Evolution For Optimization

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Today we learn about genetic algorithms and evolution in Python.

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I am one of the faithful visitors of your great contents and really appreciate your rewarding efforts and time.
I'll be grateful if you address the statistical analysis with Python as a cornerstone of datascience, if applicable.

mehdimojaradi
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Great video! I'm working more and more to optimize my work processes. And Never actually thought about using this. Thanks!

matijsbrs
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[17:08]: it's a binary state, you can keep it as simple as `genome[i] = not(genome[i])`

SolathPrime
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10:42 that's a slick generator. ty vid

phobosmoon
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it's really helpful, please it is possible to use Evolutionary algorithm to create workout plan?

dadaoluwagbenga
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another interesting video. Thanks a lot :)

gamerfisch
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I think the reason why the fitness wasn't increasing was in the function select_parent(). While higher fitness individuals may have a better chance at reproducing, it isn't likely enough for them to reproduce

raymundo
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Possibly a dumb question, but what is with the a:0 and b:0 on line 11 ? It was almost like the IDE added those in or something. If I typed them in, I got invalid syntax. If I just had randint(0, 1) instead, on line 11, it worked. Thanks.

kevinhower
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Csn you tell machine learning algorithms like candidate algorithm and decision tree algorithm

rubanruban
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I'm not sure about the select_parent() function. You are going through the pool of candidates, cumulating their respective fitness, until you hit the first candidate who's cumulated fitness is bigger than some random threshold. How does that guarantee that a candidate with a bigger fitness is statistically more often chosen over a candidate with less fitness? Shouldn't be some type of sorting? I get the impression, the candidate pool is randomly sorted; we're randomly choosing a threshold point; and therefore randomly returning any candidate that just happens to be the first to cross the (cumulated!) threshold. WDYT?

Banta
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do you think using PYGAD could make genetic algorithm easier ?

michael.adel.shafik
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I think game theory is interesting too

FelipeCantalic
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The fitness values in the one max problem were off

KernaaliKehveli
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You show interesting code, but you haven't tested it before, and are learning how it performs on-camera. How about spending an hour beforehand figuring out exactly what to show?

TomLeg
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how if the population is not binary state

fidelaneysakaulika