<jupyter_start><jupyter_text>Coursework 2: Clinical image classificationIn this coursework, you will work on a clinical imaging dataset. The dataset comes from [ISIC (International Skin Imaging Collaboration) 2016 Challenge](https://challenge.isic-archive.com). It consists of 900 skin lesion images, categorised into two classes: malignant lesions (melanoma) and benign lesions, as illustrated here.![](melanoma_vs_benign.jpg)To faciliate this coursework, we have pre-processed the images for you, including resizing the original images to a standard size of 128 by 128, splitting into a training set and a test set, so you only need to focus on the classification task. Your task here is to train a model that can classify between the malignant and benign lesions.<jupyter_code># Load the libraries (provided)
# Note: you can import more libraries
import os
import imageio
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
import sklearn
from sklearn import neighbors, metrics<jupyter_output><empty_output>
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