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  1. Introduction

   001. Why TensorFlow.mp4

   002. What you should know.mp4

   003. What is TensorFlow.mp4

  2. NLP and Transformers

   004. What is NLP.mp4

   005. Transformers for NLP.mp4

   006. Transformers, their use, and history.mp4

   007. Challenge NLP model size.mp4

   008. Solution NLP model size.mp4

  3. BERT and Transfer Learning

   009. Bias in BERT and GPT.mp4

   010. How was BERT trained.mp4

   011. Transfer learning.mp4

  4. Transformers and BERT

   012. Transformer Architecture overview.mp4

   013. BERT model and tokenization.mp4

   014. Tokenizers.mp4

   015. Self-attention.mp4

   016. Multi-head attention and feedforward network.mp4

   017. Fine-tuning BERT.mp4

  5. Conclusion

   018. Next steps.mp4

  Bonus Resources.txt