https://github.com/dmarks84/coursework_project_ml-classification

Project for IBM Data Science course on Machine Learning -- Trained ML models for classification, evaluating based on a variety of metrics
https://github.com/dmarks84/coursework_project_ml-classification

classification communication data-modeling dataframes numpy pandas python scikit-learn supervised-ml

Last synced: 11 days ago
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Project for IBM Data Science course on Machine Learning -- Trained ML models for classification, evaluating based on a variety of metrics

• Host: GitHub
• URL: https://github.com/dmarks84/coursework_project_ml-classification
• Owner: dmarks84
• License: bsd-3-clause
• Created: 2024-01-17T17:14:51.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-01-17T23:24:20.000Z (12 months ago)
• Last Synced: 2024-12-23T13:17:14.381Z (11 days ago)
• Topics: classification, communication, data-modeling, dataframes, numpy, pandas, python, scikit-learn, supervised-ml
• Language: Jupyter Notebook
• Homepage:
• Size: 22.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## Project(Project_ML-Classification)

### Part of the Coursera series: IBM Data Science

    

## Summary

I used classification algorithms to create a model based on a set of training data and evaluated our testing data to determine the best model to use for prediction.  I used several algorithms (Linear Regression, KNN, Decision Trees, Logistic Regression, and SVM).  I evaluated these models using Accuracy Score, Jaccard Index, F1-Score, LogLoss, Mean Absolute Error, Mean Squared Error, R2-Score).  

## Skills (Developed & Applied)

Programming, Python, Numpy, Pandas, Scikit-learn, Dataframes, Data Modeling, Classification, Supervised ML, Communication