How Can Researchers Get Started with Unsupervised Learning in Cancer Research?
Researchers can start by familiarizing themselves with common unsupervised learning algorithms and their applications in cancer research. Open-source tools and libraries such as scikit-learn, TensorFlow, and R provide implementations of these algorithms. Collaborating with data scientists and bioinformaticians can also be beneficial in designing and interpreting unsupervised learning models.
