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Notebook created in this video can be accessed at:
colab.research...
Problem statement:
Diagnose whether the patient has breast cancer using the features (attributes) provided.
What data is available?
Features (attributes) and corresponding labels (diagnosis) as a csv file.
archive.ics.uc...)
OR
www.kaggle.com...
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass
2 class problem: B-benign or M-malignant.
Strategy: Use deep learning to train a model using features as input and labeled diagnosis (B or M) as output on the training data. Then, evaluate the accuracy on the testing data.