What is Machine Learning (ML)? Differentiate between supervised and unsupervised learning with suitable examples. Mention the applications of ML.

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ML (Machine Learning) is a part of AI where computers learn from data and improve themselves without being directly told what to do. Supervised Learning uses labeled data (data with correct answers) - e.g., an image recognition system trained on pictures already labeled 'cat' or 'dog' can later identify a new picture correctly. Unsupervised Learning uses unlabeled data - e.g., a machine given many unlabeled photos automatically groups similar-looking nature photos together and face photos together. Applications of ML: recommendation systems (YouTube, Netflix), search engines (Google autocomplete), healthcare (disease detection), finance (fraud detection), self-driving cars, and voice recognition.