Predictive Analysis using Supervised Learning in Data Science

Perform predictive analysis on Housing Data & Breast Cancer Datasets Using Supervised Learning Techniques of Data Science in Python

Goal

Predictive, comparative and variance analysis of housing and breast cancer data (data source- University of California Irvin) by applying supervised learning techniques namely univariate and multivariate linear regression, logistic regression, and random forest

Tools

Python 3, Jupyter IPython Notebook, Anaconda, Pandas, NumPy, ScikitLearn, matplotlib

Credit

• Submitted for credit towards SER 516: Software Enterprise: Process and Project management (Data Science) at Arizona State University [Spring 2017]
• Instructor: Dr. Arbi Gazarian, Arizona State University

Resources

• Project Jupyter website
• Online Demo at try.jupyter.org
• Documentation for Jupyter notebook
• [PDF]
• Technical support - Jupyter Google Group
• Housing dataset