Karkinos Healthcare Interview Questions and Answers

ML should be used when there is a large amount of data and complex patterns to be analyzed.

• Use ML when there is a need to make predictions or decisions based on data

• ML is suitable for tasks like image recognition, natural language processing, and recommendation systems

• Avoid using ML for simple rule-based tasks that can be easily programmed

• Consider the trade-offs between accuracy and interpretability when deciding to us

Supervised, Unsupervised, Reinforcement Learning

• Supervised Learning: Uses labeled data to train the model (e.g. linear regression, decision trees)

• Unsupervised Learning: Finds patterns in unlabeled data (e.g. clustering, dimensionality reduction)

• Reinforcement Learning: Learns through trial and error by receiving rewards or penalties (e.g. Q-learning, Deep Q Networks)