Transformer Models - Natural Language Processing | Lecture Notes - YNetStudyHub
Natural Language Processing

Transformer Models

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State-of-the-art deep learning models like BERT, GPT, and Transformer-XL for various NLP tasks, utilizing self-attention mechanisms to capture long-range dependencies and achieve outstanding performance on tasks like language understanding and generation.

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Unit Syllabus 30 Topics
1
Introduction to Natural Language Processing
Text Preprocessing in NLP
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Language Models in NLP
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Sentiment Analysis
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Named Entity Recognition (NER)
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Text Classification
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Sequence-to-Sequence Models
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Transformer Models
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Text Generation
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Ethical Considerations in NLP
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Introduction to Natural Language Processing
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Preprocessing Text Data
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Text Classification
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Named Entity Recognition
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Sentiment Analysis
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Language Modeling
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Word Embeddings
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Sequence-to-Sequence Models
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Transformer Models
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Ethical Considerations in NLP
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Introduction to Natural Language Processing
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Text Preprocessing in NLP
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Language Modeling and Word Embeddings
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Named Entity Recognition
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Sentiment Analysis
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Text Classification
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Machine Translation
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Natural Language Generation
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Chatbots and Conversational Agents
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Ethical and Social Implications of NLP
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