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Natural Language Processing (NLP) is a field that helps computers understand and work with human language. With NLP, computers can perform tasks like answering questions, translating languages, summarizing texts, and recognizing speech. This is achieved by combining knowledge from linguistics (the study of language), artificial intelligence (AI), and computer science.
Language models are algorithms used in NLP to predict how words and phrases are likely to follow each other. For example, they help computers understand the structure of sentences and can predict the next word in a sentence. This technology is behind many features like autocorrect, speech recognition, and translation services.
The Natural Language Toolkit (NLTK) is a library in Python designed for working with human language data. It provides tools for text processing tasks such as breaking text into words (tokenization), analyzing sentence structure (parsing), and understanding meanings (semantic analysis). NLTK is a useful library for anyone interested in performing NLP tasks with Python.
Text similarity is a task where you determine how similar two pieces of text are. Using NLTK, you can analyze texts to see if they convey similar meanings, even if they use different words. This is useful for applications like detecting duplicate content or finding similar documents.
Language models in Python can predict what words or phrases are likely to come next in a sentence. For example, if you're typing and the model predicts and suggests the next word, this is the result of a language model at work. This technology is commonly used in text editors and messaging apps to help complete sentences or correct spelling errors.
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Welcome to our comprehensive collection of programming language cheatsheets! Whether you're a seasoned developer or a beginner, these quick reference guides provide essential tips and key information for all major languages. They focus on core concepts, commands, and functions—designed to enhance your efficiency and productivity.
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