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#OFN Natural Language Processing (NLP) 📚 NLP is a critical subset of AI that deals with the interaction between computers and human languages. It enables machines to process and understand human language. Text Classification: Description: Assigning predefined categories to text data. Applications: Sentiment analysis, email spam detection, and topic categorization. Named Entity Recognition (NER): Description: Identifying specific entities (like people, places, organizations) in text. Applications: Extracting entities from news articles, legal documents, and social media posts. Machine Translation: Description: Automatically translating text from one language to another. Applications: Google Translate, real-time translation in applications, and multilingual #chatbots . Speech Recognition: Description: Converting spoken language into text. Applications: Virtual assistants (e.g., Siri, Alexa), transcription services, and voice-controlled devices. Text Generation: Description: Creating new text based on a given prompt. Applications: Chatbots, automated content generation, and language models like GPT-3.
#OFN Natural Language Processing (NLP) 📚
NLP is a critical subset of AI that deals with the interaction between computers and human languages. It enables machines to process and understand human language.

Text Classification:

Description: Assigning predefined categories to text data.
Applications: Sentiment analysis, email spam detection, and topic categorization.
Named Entity Recognition (NER):

Description: Identifying specific entities (like people, places, organizations) in text.
Applications: Extracting entities from news articles, legal documents, and social media posts.
Machine Translation:

Description: Automatically translating text from one language to another.
Applications: Google Translate, real-time translation in applications, and multilingual #chatbots .
Speech Recognition:

Description: Converting spoken language into text.
Applications: Virtual assistants (e.g., Siri, Alexa), transcription services, and voice-controlled devices.
Text Generation:

Description: Creating new text based on a given prompt.
Applications: Chatbots, automated content generation, and language models like GPT-3.
#OFN Recurrent Neural Network (RNN) Structure: Contains loops within its layers to process sequential data. Use Case: Time-series forecasting, natural language processing. Example in OFN: #Chatbots or AI-driven customer support powered by #OFN .
#OFN Recurrent Neural Network (RNN)
Structure: Contains loops within its layers to process sequential data.
Use Case: Time-series forecasting, natural language processing.
Example in OFN: #Chatbots or AI-driven customer support powered by #OFN .
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