We will work on a problem of classification to predict whether a cancer is benign or malignant. We will drive through developing an algorithm that uses neural networks to accurately predict (~94 percent accuracy) if a breast cancer tumor is benign or malignant, basically teaching a machine to predict breast cancer. This may seem difficult, but using Keras APIs, we will have this seemingly complex model ready for use. The dataset description is provided in the following content:
Breast Cancer Wisconsin (Diagnostic) dataset:
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. A few of the images can be found at http://www.cs.wisc.edu/~street/images/.
Class distribution: 357 benign, 212 malignant.
This database is also available...
