Natural Language Processing With Transformers in Python

Creation Time	April 13, 2024, 3:46 p.m.
Last Access Time	June 15, 2025, 2:24 a.m.
File Size	3.3 GB
Keywords	Natural Language Python Processing in Transformers With
Total Requests	66
Total Files	113
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07 Long Text Classification With BERT/001 Classification of Long Text Using Windows.mp4 116.1 MB
08 Named Entity Recognition (NER)/008 NER With Sentiment.mp4 99.9 MB
08 Named Entity Recognition (NER)/004 Pulling Data With The Reddit API.mp4 88.9 MB
07 Long Text Classification With BERT/002 Window Method in PyTorch.mp4 84.9 MB
14 Fine-Tuning Transformer Models/005 The Logic of MLM.mp4 79.4 MB
14 Fine-Tuning Transformer Models/010 Fine-tuning with NSP - Data Preparation.mp4 78.0 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/006 Build and Save.mp4 77.0 MB
14 Fine-Tuning Transformer Models/006 Fine-tuning with MLM - Data Preparation.mp4 76.7 MB
11 Reader-Retriever QA With Haystack/013 Retriever-Reader Stack.mp4 75.3 MB
14 Fine-Tuning Transformer Models/007 Fine-tuning with MLM - Training.mp4 69.7 MB
11 Reader-Retriever QA With Haystack/010 FAISS in Haystack.mp4 68.1 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/003 Preprocessing.mp4 62.5 MB
08 Named Entity Recognition (NER)/009 NER With roBERTa.mp4 59.0 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/007 Loading and Prediction.mp4 56.8 MB
12 [Project] Open-Domain QA/003 Building the Haystack Pipeline.mp4 55.8 MB
02 NLP and Transformers/009 Positional Encoding.mp4 55.5 MB
05 Language Classification/004 Tokenization And Special Tokens For BERT.mp4 55.4 MB
08 Named Entity Recognition (NER)/001 Introduction to spaCy.mp4 51.6 MB
04 Attention/002 Alignment With Dot-Product.mp4 49.1 MB
14 Fine-Tuning Transformer Models/003 BERT Pretraining - Masked-Language Modeling (MLM).mp4 46.7 MB
09 Question and Answering/006 Our First Q&A Model.mp4 45.7 MB
14 Fine-Tuning Transformer Models/013 Fine-tuning with MLM and NSP - Data Preparation.mp4 43.6 MB
11 Reader-Retriever QA With Haystack/009 What is FAISS_.mp4 42.9 MB
12 [Project] Open-Domain QA/002 Creating the Database.mp4 42.4 MB
14 Fine-Tuning Transformer Models/004 BERT Pretraining - Next Sentence Prediction (NSP).mp4 42.1 MB
02 NLP and Transformers/010 Transformer Heads.mp4 39.8 MB
11 Reader-Retriever QA With Haystack/005 Elasticsearch in Haystack.mp4 39.0 MB
09 Question and Answering/004 Processing SQuAD Training Data.mp4 38.4 MB
05 Language Classification/001 Introduction to Sentiment Analysis.mp4 37.5 MB
01 Introduction/003 Environment Setup.mp4 37.3 MB
08 Named Entity Recognition (NER)/003 Authenticating With The Reddit API.mp4 35.6 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/002 Getting the Data (Kaggle API).mp4 35.0 MB
01 Introduction/002 Course Overview.mp4 34.4 MB
10 Metrics For Language/003 Applying ROUGE to Q&A.mp4 33.9 MB
13 Similarity/004 Using Cosine Similarity.mp4 33.9 MB
04 Attention/006 Multi-head and Scaled Dot-Product Attention.mp4 33.8 MB
08 Named Entity Recognition (NER)/002 Extracting Entities.mp4 33.5 MB
02 NLP and Transformers/002 Pros and Cons of Neural AI.mp4 32.8 MB
13 Similarity/003 Sentence Vectors With Mean Pooling.mp4 32.1 MB
05 Language Classification/002 Prebuilt Flair Models.mp4 30.7 MB
03 Preprocessing for NLP/009 Unicode Normalization - NFKD and NFKC.mp4 30.4 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/005 Dataset Shuffle, Batch, Split, and Save.mp4 30.2 MB
09 Question and Answering/005 (Optional) Processing SQuAD Training Data with Match-Case.mp4 30.1 MB
13 Similarity/002 Extracting The Last Hidden State Tensor.mp4 29.7 MB
11 Reader-Retriever QA With Haystack/011 What is DPR_.mp4 29.7 MB
14 Fine-Tuning Transformer Models/002 Introduction to BERT For Pretraining Code.mp4 29.3 MB
04 Attention/003 Dot-Product Attention.mp4 29.0 MB
09 Question and Answering/002 Retrievers, Readers, and Generators.mp4 28.7 MB
14 Fine-Tuning Transformer Models/001 Visual Guide to BERT Pretraining.mp4 28.6 MB
04 Attention/004 Self Attention.mp4 28.4 MB
13 Similarity/001 Introduction to Similarity.mp4 28.2 MB
08 Named Entity Recognition (NER)/005 Extracting ORGs From Reddit Data.mp4 28.1 MB
05 Language Classification/003 Introduction to Sentiment Models With Transformers.mp4 26.9 MB
11 Reader-Retriever QA With Haystack/007 Cleaning the Index.mp4 26.4 MB
14 Fine-Tuning Transformer Models/012 The Logic of MLM and NSP.mp4 26.3 MB
05 Language Classification/005 Making Predictions.mp4 26.0 MB
09 Question and Answering/003 Intro to SQuAD 2.0.mp4 25.4 MB
02 NLP and Transformers/006 Encoder-Decoder Attention.mp4 25.2 MB
03 Preprocessing for NLP/002 Tokens Introduction.mp4 24.0 MB
01 Introduction/005 CUDA Setup.mp4 23.7 MB
11 Reader-Retriever QA With Haystack/002 What is Elasticsearch_.mp4 23.5 MB
03 Preprocessing for NLP/001 Stopwords.mp4 23.0 MB
13 Similarity/005 Similarity With Sentence-Transformers.mp4 23.0 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/004 Building a Dataset.mp4 22.6 MB
02 NLP and Transformers/001 The Three Eras of AI.mp4 22.2 MB
02 NLP and Transformers/003 Word Vectors.mp4 21.7 MB
10 Metrics For Language/002 ROUGE in Python.mp4 21.7 MB
10 Metrics For Language/004 Recall, Precision and F1.mp4 21.0 MB
11 Reader-Retriever QA With Haystack/003 Elasticsearch Setup (Windows).mp4 20.9 MB
14 Fine-Tuning Transformer Models/009 The Logic of NSP.mp4 20.9 MB
02 NLP and Transformers/007 Self-Attention.mp4 20.8 MB
11 Reader-Retriever QA With Haystack/006 Sparse Retrievers.mp4 20.4 MB
03 Preprocessing for NLP/007 Unicode Normalization - Composition and Decomposition.mp4 20.3 MB
11 Reader-Retriever QA With Haystack/004 Elasticsearch Setup (Linux).mp4 20.2 MB
08 Named Entity Recognition (NER)/007 Entity Blacklist.mp4 20.1 MB
03 Preprocessing for NLP/008 Unicode Normalization - NFD and NFC.mp4 20.0 MB
14 Fine-Tuning Transformer Models/008 Fine-tuning with MLM - Training with Trainer.mp4 19.9 MB
03 Preprocessing for NLP/003 Model-Specific Special Tokens.mp4 18.9 MB
10 Metrics For Language/006 Q&A Performance With ROUGE.mp4 18.7 MB
08 Named Entity Recognition (NER)/006 Getting Entity Frequency.mp4 18.4 MB
10 Metrics For Language/001 Q&A Performance With Exact Match (EM).mp4 18.2 MB
03 Preprocessing for NLP/004 Stemming.mp4 17.2 MB
02 NLP and Transformers/004 Recurrent Neural Networks.mp4 17.1 MB
03 Preprocessing for NLP/006 Unicode Normalization - Canonical and Compatibility Equivalence.mp4 17.0 MB
09 Question and Answering/001 Open Domain and Reading Comprehension.mp4 16.1 MB
04 Attention/001 Attention Introduction.mp4 15.8 MB
10 Metrics For Language/005 Longest Common Subsequence (LCS).mp4 15.0 MB
11 Reader-Retriever QA With Haystack/012 The DPR Architecture.mp4 14.3 MB
14 Fine-Tuning Transformer Models/011 Fine-tuning with NSP - DataLoader.mp4 14.3 MB
11 Reader-Retriever QA With Haystack/001 Intro to Retriever-Reader and Haystack.mp4 13.9 MB
02 NLP and Transformers/008 Multi-head Attention.mp4 13.3 MB
11 Reader-Retriever QA With Haystack/008 Implementing a BM25 Retriever.mp4 12.5 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/001 Project Overview.mp4 12.5 MB
04 Attention/005 Bidirectional Attention.mp4 10.8 MB
03 Preprocessing for NLP/005 Lemmatization.mp4 10.6 MB
01 Introduction/001 Introduction.mp4 9.2 MB
02 NLP and Transformers/005 Long Short-Term Memory.mp4 6.3 MB
12 [Project] Open-Domain QA/001 ODQA Stack Structure.mp4 6.2 MB
01 Introduction/004 Alternative Setup.html 2.8 KB
11 Reader-Retriever QA With Haystack/external-assets-links.txt 1.8 KB
08 Named Entity Recognition (NER)/external-assets-links.txt 1.3 KB
14 Fine-Tuning Transformer Models/external-assets-links.txt 1.3 KB
03 Preprocessing for NLP/external-assets-links.txt 1003 bytes
09 Question and Answering/external-assets-links.txt 886 bytes
06 [Project] Sentiment Model With TensorFlow and Transformers/external-assets-links.txt 805 bytes
04 Attention/external-assets-links.txt 760 bytes
05 Language Classification/external-assets-links.txt 680 bytes
10 Metrics For Language/external-assets-links.txt 680 bytes
Downloaded from 1337x.html 543 bytes
07 Long Text Classification With BERT/external-assets-links.txt 409 bytes
02 NLP and Transformers/external-assets-links.txt 379 bytes
01 Introduction/external-assets-links.txt 372 bytes
12 [Project] Open-Domain QA/external-assets-links.txt 366 bytes

Natural Language Processing With Transformers in Python

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