Breast-Cancer-Diagnostic-Classification

In this project, I experimented with various machine learning algorithms on a dataset from Breast Cancer Wisconsin (Diagnostic) Data available on UCI repository and kaggle. This dataset provides various features along with a target variable of diagnosis. I learned how different machine learning techniques can be applied to find the patterns in the data and classify the tumor as benign or malignant. Through this project, I gained a lot of experience in data wrangling, feature engineering and machine learning algorithms, and compare the results obtained on different ML models based on accuracy and ROC-AUC.