Classification-using-MachineLearning-Python

Learning Objectives

Apply the K Nearest Neighbors algorithm.
Describe model evaluation metrics.
Decision Tree.
Logistic Regression.
Support Vector Machine.
Apply Classification algorithms on various datasets to solve real world problems.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
ChurnData.csv		ChurnData.csv
Classification-Decision-Trees-drug-Delowar.ipynb		Classification-Decision-Trees-drug-Delowar.ipynb
Classification-Decision-Trees-drug-Delowar.py		Classification-Decision-Trees-drug-Delowar.py
Classification-K-Nearest-neighbors-CustCat-Delowar.ipynb		Classification-K-Nearest-neighbors-CustCat-Delowar.ipynb
Classification-K-Nearest-neighbors-CustCat-Delowar.py		Classification-K-Nearest-neighbors-CustCat-Delowar.py
Classification-Logistic-Regression-churn-Delowar.ipynb		Classification-Logistic-Regression-churn-Delowar.ipynb
Classification-Logistic-Regression-churn-Delowar.py		Classification-Logistic-Regression-churn-Delowar.py
Classification-SVM-cancer-Delowar.ipynb		Classification-SVM-cancer-Delowar.ipynb
Classification-SVM-cancer-Delowar.py		Classification-SVM-cancer-Delowar.py
README.md		README.md
cell_samples.csv		cell_samples.csv
drug200.csv		drug200.csv
teleCust1000t.csv		teleCust1000t.csv

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