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Data Science Models

Final Project - Brayden CumminsFor this final project I am going to be looking at a dataset of Data Science Salaries in 2023 and using a country codes CSV to get the countries full name. Data Science ModelsAt least 2 different Data Science models, appropriate for the data.I trained 2 models, one was a decision tree learner that predicts the company size. The second isa Random Forest Learner (Regression) that predicts ones salary. Both use the joined data thatwas cleaned and manipulated on the second page. Final Brayden CumminsMy plan for this final was to work around this data science salary dataset and try and showdiffernet visualizations based on that data that was in here. I added the countries dataset to getmore data for what countires were which.The first page is me cleaning and bringing in the two datasets.The second page was me Manipulating the data (Joining it and grouping before visulizations) andvisualizing the data with differnet charts.The last page I trained 2 models to predict the company size and salary. Overall this was a pretty interesting final, and I learned a lot with this class. I tried to explain what Iwas doing under each node to help with documentation and the outcomes. Thanks for anamazing semester! 70/30 splitPredict Company SizeEvaluate model accuracyEvaluate model accuracydrawing randompredict salary Read and ManipulateJoined Data Partitioning DecisionTree Learner Decision TreePredictor Scorer (JavaScript) Random Forest Predictor(Regression) Numeric Scorer Partitioning Read and ManipulateJoined Data Random Forest Learner(Regression) Final Project - Brayden CumminsFor this final project I am going to be looking at a dataset of Data Science Salaries in 2023 and using a country codes CSV to get the countries full name. Data Science ModelsAt least 2 different Data Science models, appropriate for the data.I trained 2 models, one was a decision tree learner that predicts the company size. The second isa Random Forest Learner (Regression) that predicts ones salary. Both use the joined data thatwas cleaned and manipulated on the second page. Final Brayden CumminsMy plan for this final was to work around this data science salary dataset and try and showdiffernet visualizations based on that data that was in here. I added the countries dataset to getmore data for what countires were which.The first page is me cleaning and bringing in the two datasets.The second page was me Manipulating the data (Joining it and grouping before visulizations) andvisualizing the data with differnet charts.The last page I trained 2 models to predict the company size and salary. Overall this was a pretty interesting final, and I learned a lot with this class. I tried to explain what Iwas doing under each node to help with documentation and the outcomes. Thanks for anamazing semester! 70/30 splitPredict Company SizeEvaluate model accuracyEvaluate model accuracydrawing randompredict salaryRead and ManipulateJoined Data Partitioning DecisionTree Learner Decision TreePredictor Scorer (JavaScript) Random Forest Predictor(Regression) Numeric Scorer Partitioning Read and ManipulateJoined Data Random Forest Learner(Regression)

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Created by: Brayd
Created at: 2023-04-13
On NodePit since: 2023-04-14
Last update: 2024-04-28
Created with KNIME version: v4.7.0

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