fshipy / Predict_Mammographic_Mass

Using Different Techniques in Machine Learning to Predict the Severity of a Mammographic Mass

Predict_Mammographic_Mass (In Progress)

This project is assigned by Frank Kane in Machine Learning, Data Science and Deep Learning with Python (Udemy Course).

Dataset is from the UCI repository (Source: https://archive.ics.uci.edu/ml/datasets/Mammographic+Mass)

Purpose: Using different techniques in Machine Learning to predict the severity of a Mammographic Mass and comparing the predicting accuracy.

What techniques will be included: 1.Decision tree 2.Random forest 3.KNN 4.Naive Bayes 5.SVM 6.Logistic Regression 7.Neural network using Keras.