This repository contains Breast cancer classification algorithm using machine learning techniques in python.

Breast Cancer : As per 'American Cancer Society' Breast cancer is the second leading cause of the cancer death in women. About 1 in 38 women has a chance of dying with breast cancer. Early detection of breast cancer can save many lives.

Dataset : The dataset used in this repo is from sklearn module. This dataset contains 569 rows and 30 numeric columns and one class that specifies whether the tumor is malignant or benign. The values in the dataset may be derived using the images of the tumor and then converting that images to data. There are no missing values in the dataset.

Algorithm : The algorithm used in this dataset is Support Vector Machines. (We can use other models like Logistic Regression as well instead of SVM)

Visualisation : The library used for visualizing the data, confusion matrix etc. is seaborn.

This code is prepared using Jupyter Notebook.

Deployment : Apply model deployment using Flask and Docker