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Job Satisfaction Analysis #302

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merged 2 commits into from
Jun 27, 2024
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ranamanish674zu
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Target Variable: JobSatisfaction or CareerSatisfaction.
Predictors: Variables like Employment, YearsCodingProf, FormalEducation, CompanySize, DevType, etc.
Objective: Predict levels of job satisfaction based on personal and professional attributes
Predicting job satisfaction enables organizations to enhance employee well-being, reduce turnover, improve performance, tailor recruitment strategies, and foster a positive workplace culture.
here are some screenshot from the ipynb file->
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@sanjay-kv complete issue #293 please review

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Welcome to Our repository.🎊 Thank you so much for taking the time to point this out.

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this is not the right approach, you should be adding like enhancement to existing ipynb file. or web app.

@ranamanish674zu
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this is not the right approach, you should be adding like enhancement to existing ipynb file. or web app.

okay sir

@ranamanish674zu
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@sanjay-kv i have added a web app with streamlit on pkl model ....could you please review

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you are creating folder structure similar to documentation repos like machine learning repo. this is a deployment issue so here we should work on the enhancement of the existing project.

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you are creating folder structure similar to documentation repos like machine learning repo. this is a deployment issue so here we should work on the enhancement of the existing project.

@sanjay-kv do you mean i have to edit the folders which are stored in backlog folder according to my changes ?is it right sir ??

@sanjay-kv sanjay-kv merged commit 5b1b18a into recodehive:main Jun 27, 2024
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🎉 Your pull request has been successfully merged! 🎉 Thank you for your valuable contribution to our project. Your efforts are greatly appreciated. Feel free to reach out if you have any more contributions or if there's anything else we can assist you with. Keep up the fantastic work! 🚀

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