Data, The raw information, like text or numbers, that computers use to learn things., Pattern, A repeating sequence or shape in data that helps a computer make a prediction., AI (Artificial Intelligence), The broad science of making computers act and think like humans., Natural Language Processing (NLP), A branch of AI that teaches computers how to understand and talk in human languages., Corpus, A very large collection of written or spoken texts used to train a computer., Algorithm, A step-by-step set of instructions or rules that a computer follows to solve a problem., Model, A mathematical "brain" created by an algorithm that has finished its training on data., Token, A small piece of text, like a single word or a character, that a computer processes., Tagging, The process of labeling a word with its part of speech, like marking "run" as a verb., Semantic, The study of the actual meaning of words and sentences rather than just their spelling., Ambiguity, When a word or sentence has more than one meaning, which can confuse a computer., Translation, Using a computer to change text from one language into another language., Auto-correct, A tool that identifies misspelled words and automatically fixes them for you., Summarization, Taking a long piece of text and shrinking it down to just the most important points., Reporting, The process of gathering data and presenting it in a clear, organized way., Chatbot, A computer program designed to have a conversation with a human via text or voice., Sentiment Analysis, Figuring out if a piece of writing feels happy, sad, angry, or neutral., Language Model, A system trained to predict which word is most likely to come next in a sentence., Large Language Model (LLM), A massive model trained on huge amounts of internet text to handle complex tasks..

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