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Natural Language Processing With Transformers in Python

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  2. File Size：3.36 GB
  3. Creat Time：2024-06-04
  4. Active Degree：44
  5. Last Active：2024-10-30
  6. File Tags：Natural  Language  Processing  With  Transformers  in  Python  
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File List:

    Natural Language Processing With Transformers in Python

  1. 07 Long Text Classification With BERT/001 Classification of Long Text Using Windows.mp4 118.93 MB
  2. 08 Named Entity Recognition (NER)/008 NER With Sentiment.mp4 102.27 MB
  3. 08 Named Entity Recognition (NER)/004 Pulling Data With The Reddit API.mp4 91.08 MB
  4. 07 Long Text Classification With BERT/002 Window Method in PyTorch.mp4 86.98 MB
  5. 14 Fine-Tuning Transformer Models/005 The Logic of MLM.mp4 81.31 MB
  6. 14 Fine-Tuning Transformer Models/010 Fine-tuning with NSP - Data Preparation.mp4 79.84 MB
  7. 06 [Project] Sentiment Model With TensorFlow and Transformers/006 Build and Save.mp4 78.86 MB
  8. 14 Fine-Tuning Transformer Models/006 Fine-tuning with MLM - Data Preparation.mp4 78.56 MB
  9. 11 Reader-Retriever QA With Haystack/013 Retriever-Reader Stack.mp4 77.06 MB
  10. 14 Fine-Tuning Transformer Models/007 Fine-tuning with MLM - Training.mp4 71.36 MB
  11. 11 Reader-Retriever QA With Haystack/010 FAISS in Haystack.mp4 69.72 MB
  12. 06 [Project] Sentiment Model With TensorFlow and Transformers/003 Preprocessing.mp4 63.98 MB
  13. 08 Named Entity Recognition (NER)/009 NER With roBERTa.mp4 60.42 MB
  14. 06 [Project] Sentiment Model With TensorFlow and Transformers/007 Loading and Prediction.mp4 58.12 MB
  15. 12 [Project] Open-Domain QA/003 Building the Haystack Pipeline.mp4 57.14 MB
  16. 02 NLP and Transformers/009 Positional Encoding.mp4 56.85 MB
  17. 05 Language Classification/004 Tokenization And Special Tokens For BERT.mp4 56.76 MB
  18. 08 Named Entity Recognition (NER)/001 Introduction to spaCy.mp4 52.88 MB
  19. 04 Attention/002 Alignment With Dot-Product.mp4 50.30 MB
  20. 14 Fine-Tuning Transformer Models/003 BERT Pretraining - Masked-Language Modeling (MLM).mp4 47.83 MB
  21. 09 Question and Answering/006 Our First Q&A Model.mp4 46.81 MB
  22. 14 Fine-Tuning Transformer Models/013 Fine-tuning with MLM and NSP - Data Preparation.mp4 44.66 MB
  23. 11 Reader-Retriever QA With Haystack/009 What is FAISS_.mp4 43.92 MB
  24. 12 [Project] Open-Domain QA/002 Creating the Database.mp4 43.44 MB
  25. 14 Fine-Tuning Transformer Models/004 BERT Pretraining - Next Sentence Prediction (NSP).mp4 43.08 MB
  26. 02 NLP and Transformers/010 Transformer Heads.mp4 40.76 MB
  27. 11 Reader-Retriever QA With Haystack/005 Elasticsearch in Haystack.mp4 39.96 MB
  28. 09 Question and Answering/004 Processing SQuAD Training Data.mp4 39.33 MB
  29. 05 Language Classification/001 Introduction to Sentiment Analysis.mp4 38.42 MB
  30. 01 Introduction/003 Environment Setup.mp4 38.14 MB
  31. 08 Named Entity Recognition (NER)/003 Authenticating With The Reddit API.mp4 36.48 MB
  32. 06 [Project] Sentiment Model With TensorFlow and Transformers/002 Getting the Data (Kaggle API).mp4 35.85 MB
  33. 01 Introduction/002 Course Overview.mp4 35.20 MB
  34. 10 Metrics For Language/003 Applying ROUGE to Q&A.mp4 34.75 MB
  35. 13 Similarity/004 Using Cosine Similarity.mp4 34.67 MB
  36. 04 Attention/006 Multi-head and Scaled Dot-Product Attention.mp4 34.64 MB
  37. 08 Named Entity Recognition (NER)/002 Extracting Entities.mp4 34.33 MB
  38. 02 NLP and Transformers/002 Pros and Cons of Neural AI.mp4 33.57 MB
  39. 13 Similarity/003 Sentence Vectors With Mean Pooling.mp4 32.86 MB
  40. 05 Language Classification/002 Prebuilt Flair Models.mp4 31.43 MB
  41. 03 Preprocessing for NLP/009 Unicode Normalization - NFKD and NFKC.mp4 31.15 MB
  42. 06 [Project] Sentiment Model With TensorFlow and Transformers/005 Dataset Shuffle, Batch, Split, and Save.mp4 30.88 MB
  43. 09 Question and Answering/005 (Optional) Processing SQuAD Training Data with Match-Case.mp4 30.82 MB
  44. 13 Similarity/002 Extracting The Last Hidden State Tensor.mp4 30.46 MB
  45. 11 Reader-Retriever QA With Haystack/011 What is DPR_.mp4 30.37 MB
  46. 14 Fine-Tuning Transformer Models/002 Introduction to BERT For Pretraining Code.mp4 29.96 MB
  47. 04 Attention/003 Dot-Product Attention.mp4 29.68 MB
  48. 09 Question and Answering/002 Retrievers, Readers, and Generators.mp4 29.37 MB
  49. 14 Fine-Tuning Transformer Models/001 Visual Guide to BERT Pretraining.mp4 29.28 MB
  50. 04 Attention/004 Self Attention.mp4 29.08 MB
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