Currently there are no examples showing how pytorch was used to develop machine learning models to classify tumors as either malignant or benign. This jupyter notebook shall contain some details on the reason why the tumor classifier was created, what the process behind this procedure was, how the data was transformed, and how the model was created.
The results and the metrics will also be a reflection of how the library was used to classify tumors and measure the performance of the machine learning model.
Currently there are no examples showing how pytorch was used to develop machine learning models to classify tumors as either malignant or benign. This jupyter notebook shall contain some details on the reason why the tumor classifier was created, what the process behind this procedure was, how the data was transformed, and how the model was created.
The results and the metrics will also be a reflection of how the library was used to classify tumors and measure the performance of the machine learning model.