Cancer Genomics | Neural Networks vs k-NN Classifiers

Compare neural networks and k-NN in cancer genomics by building and evaluating a k-NN classifier on the breast cancer dataset using scikit-learn, with data loading, training, and train-test split.

Explore k-nearest neighbors for breast cancer data using pandas to load Wisconsin dataset, visualize with plots, and evaluate training and test accuracy, finding six neighbors yields the best test performance.

Compare neural networks and k-nearest neighbors on a breast cancer data set, showing how scaling improves an MLP's accuracy to 99.5% training and 96% test, vs. kNN.

Explore dna sequence basics, counting bases and computing gc content, then translate dna to rna and protein using user-entered sequences.