📝 Natural Language Processing (NLP) is the process of enabling computers to understand and process human language.
🤔 NLP begins with unstructured text, which is transformed into structured data that computers can analyze.
💡 NLP has high utility in various AI applications and can be utilized to enhance inventing processes.
🔑 NLP translates between structured and unstructured data.
💡 NLU focuses on converting unstructured data to structured data.
🌐 NLP is used in machine translation to understand the context of sentences.
🌍 NLP is important in translation to avoid misinterpretations and preserve the intended meaning.
💬 Virtual assistants and chatbots utilize NLP to understand and respond to human language.
😊 Sentiment analysis is another application of NLP to determine the positive or negative emotions expressed in text.
✨ NLP (Natural Language Processing) is a field that focuses on understanding and analyzing human language.
📧 NLP can be applied to tasks such as sentiment analysis, sarcasm detection, and spam detection.
⚙️ NLP utilizes a variety of tools and algorithms to process and analyze unstructured text.
🔠 NLP (Natural Language Processing) involves working with tokens and stems.
🌱 Stemming is a technique to derive the word stem by removing prefixes and suffixes from tokens.
📚 Lemmatization uses dictionary definitions to derive the root or lemma of a token.
🔍 Part of speech tagging identifies the function of a word based on its context within a sentence.
👥 Named entity recognition identifies entities associated with specific tokens, such as locations or names.
💻 These tools are part of the process of converting unstructured human speech into structured data that can be understood by computers.
📚 NLP is a field of study that focuses on how computers can understand and process human language.
🔍 It involves techniques like text classification, sentiment analysis, and machine translation.
💡 NLP has various applications in areas like customer support, virtual assistants, and language translation.
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