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