iitsasim/predictingbreastcancerusingdeeplearningng-breast-cancer-tumor

Predicting Cancer Malignancy with a 2 layer neural network coded from scratch in Python.

Access the code with this link
Python Jupyter Notebook

This notebook holds the Python code connected to this 3 part article:

Part 1 | Part 2 | Part 3

With this code and the associated articles, you are going to:

• Create a neural network from scratch in Python. Train it using the gradient descent algorithm.
• Apply that basic network to The Wisconsin Cancer Data-set. Predict if a tumor is benign or malignant, based on 9 different features.
• Explore deeply how back-propagation and gradient descent work.
• Review the basics and explore advanced concepts.

The data comes from The Wisconsin Cancer Data-set.
This data was gathered by the University of Wisconsin Hospitals, Madison and by Dr. William H. Wolberg.
By request of the owners of the data: we mention one of the studies linked to the data-set: O. L. Mangasarian and W. H. Wolberg: "Cancer diagnosis via linear programming", SIAM News, Volume 23, Number 5, September 1990, pp 1 & 18.