DART

DART

Duration: 6 Months
    • Introduction to BART
    • Overview of Transformer Models
    • Bidirectional Encoding: Understanding BERT
    • Auto-Regressive Decoding: Understanding GPT
    • BART Architecture: Combining BERT and GPT
    • Training BART: Pre-training and Fine-tuning
    • Text Generation with BART
    • Text Summarization using BART
    • Text-to-Text Transfer Learning
    • Applications of BART in NLP Tasks
    • BART for Sequence-to-Sequence Tasks
    • Preprocessing Data for BART Models
    • Training and Fine-Tuning BART on Custom Datasets
    • Evaluating BART Model Performance
    • Advanced Applications of BART (e.g., Translation, Question Answering)
    • Comparison of BART with Other NLP Models (e.g., T5, BERT, GPT)
    • BART Model Fine-tuning with Hugging Face Transformers
    • Deploying BART Models in Production
    • Challenges and Limitations of BART Models
    • Recent Developments and Research in BART
    • Hands-On with BART: Building NLP Applications
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