<ul><li>Traditional programming involves giving a set of rules for computers to follow without learning.</li><li>For simple tasks like sorting numbers or calculating bills, traditional programming works well.</li><li>Machine Learning shines when rules are complex or constantly changing, like in spam email filtering.</li><li>Machine Learning comes in different types, such as supervised learning, clustering, and reinforcement learning.</li><li>Supervised learning involves providing input-output pairs for the machine to learn the relationship.</li><li>Machine Learning types also include regression, classification, clustering, and anomaly detection.</li><li>Reinforcement learning is about agents making decisions through interactions with an environment.</li><li>One approach is semi-supervised learning, helpful with small labeled data and large unlabeled data.</li><li>Machine Learning types like reinforcement learning are used in applications like game AI and autonomous driving.</li><li>Specialized subfields of Machine Learning include NLP, computer vision, deep learning, and generative AI.</li></ul>

G(I)RWM — Machine Learning Edition | Machine Learning Overview: Day 13

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