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Natural Language Processing With Transformers in Python

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File Name
Size
07 Long Text Classification With BERT/001 Classification of Long Text Using Windows.mp4
116 MB
01 Introduction/001 Introduction.mp4
9.2 MB
01 Introduction/002 Course Overview.mp4
34 MB
01 Introduction/003 Environment Setup.mp4
37 MB
01 Introduction/004 Alternative Setup.html
2.8 kB
01 Introduction/005 CUDA Setup.mp4
24 MB
01 Introduction/external-assets-links.txt
372 B
02 NLP and Transformers/001 The Three Eras of AI.mp4
22 MB
02 NLP and Transformers/002 Pros and Cons of Neural AI.mp4
33 MB
02 NLP and Transformers/003 Word Vectors.mp4
22 MB
02 NLP and Transformers/004 Recurrent Neural Networks.mp4
17 MB
02 NLP and Transformers/005 Long Short-Term Memory.mp4
6.3 MB
02 NLP and Transformers/006 Encoder-Decoder Attention.mp4
25 MB
02 NLP and Transformers/007 Self-Attention.mp4
21 MB
02 NLP and Transformers/008 Multi-head Attention.mp4
13 MB
02 NLP and Transformers/009 Positional Encoding.mp4
56 MB
02 NLP and Transformers/010 Transformer Heads.mp4
40 MB
02 NLP and Transformers/external-assets-links.txt
379 B
03 Preprocessing for NLP/001 Stopwords.mp4
23 MB
03 Preprocessing for NLP/002 Tokens Introduction.mp4
24 MB
03 Preprocessing for NLP/003 Model-Specific Special Tokens.mp4
19 MB
03 Preprocessing for NLP/004 Stemming.mp4
17 MB
03 Preprocessing for NLP/005 Lemmatization.mp4
11 MB
03 Preprocessing for NLP/006 Unicode Normalization - Canonical and Compatibility Equivalence.mp4
17 MB
03 Preprocessing for NLP/007 Unicode Normalization - Composition and Decomposition.mp4
20 MB
03 Preprocessing for NLP/008 Unicode Normalization - NFD and NFC.mp4
20 MB
03 Preprocessing for NLP/009 Unicode Normalization - NFKD and NFKC.mp4
30 MB
03 Preprocessing for NLP/external-assets-links.txt
1003 B
04 Attention/001 Attention Introduction.mp4
16 MB
04 Attention/002 Alignment With Dot-Product.mp4
49 MB
04 Attention/003 Dot-Product Attention.mp4
29 MB
04 Attention/004 Self Attention.mp4
28 MB
04 Attention/005 Bidirectional Attention.mp4
11 MB
04 Attention/006 Multi-head and Scaled Dot-Product Attention.mp4
34 MB
04 Attention/external-assets-links.txt
760 B
05 Language Classification/001 Introduction to Sentiment Analysis.mp4
38 MB
05 Language Classification/002 Prebuilt Flair Models.mp4
31 MB
05 Language Classification/003 Introduction to Sentiment Models With Transformers.mp4
27 MB
05 Language Classification/004 Tokenization And Special Tokens For BERT.mp4
55 MB
05 Language Classification/005 Making Predictions.mp4
26 MB
05 Language Classification/external-assets-links.txt
680 B
06 [Project] Sentiment Model With TensorFlow and Transformers/001 Project Overview.mp4
12 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/002 Getting the Data (Kaggle API).mp4
35 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/003 Preprocessing.mp4
62 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/004 Building a Dataset.mp4
23 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/005 Dataset Shuffle, Batch, Split, and Save.mp4
30 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/006 Build and Save.mp4
77 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/007 Loading and Prediction.mp4
57 MB
06 [Project] Sentiment Model With TensorFlow and Transformers/external-assets-links.txt
805 B
Downloaded from 1337x.html
543 B
07 Long Text Classification With BERT/002 Window Method in PyTorch.mp4
85 MB
07 Long Text Classification With BERT/external-assets-links.txt
409 B
08 Named Entity Recognition (NER)/001 Introduction to spaCy.mp4
52 MB
08 Named Entity Recognition (NER)/002 Extracting Entities.mp4
34 MB
08 Named Entity Recognition (NER)/003 Authenticating With The Reddit API.mp4
36 MB
08 Named Entity Recognition (NER)/004 Pulling Data With The Reddit API.mp4
89 MB
08 Named Entity Recognition (NER)/005 Extracting ORGs From Reddit Data.mp4
28 MB
08 Named Entity Recognition (NER)/006 Getting Entity Frequency.mp4
18 MB
08 Named Entity Recognition (NER)/007 Entity Blacklist.mp4
20 MB
08 Named Entity Recognition (NER)/008 NER With Sentiment.mp4
100 MB
08 Named Entity Recognition (NER)/009 NER With roBERTa.mp4
59 MB
08 Named Entity Recognition (NER)/external-assets-links.txt
1.3 kB
09 Question and Answering/001 Open Domain and Reading Comprehension.mp4
16 MB
09 Question and Answering/002 Retrievers, Readers, and Generators.mp4
29 MB
09 Question and Answering/003 Intro to SQuAD 2.0.mp4
25 MB
09 Question and Answering/004 Processing SQuAD Training Data.mp4
38 MB
09 Question and Answering/005 (Optional) Processing SQuAD Training Data with Match-Case.mp4
30 MB
09 Question and Answering/006 Our First Q&A Model.mp4
46 MB
09 Question and Answering/external-assets-links.txt
886 B
10 Metrics For Language/001 Q&A Performance With Exact Match (EM).mp4
18 MB
10 Metrics For Language/002 ROUGE in Python.mp4
22 MB
10 Metrics For Language/003 Applying ROUGE to Q&A.mp4
34 MB
10 Metrics For Language/004 Recall, Precision and F1.mp4
21 MB
10 Metrics For Language/005 Longest Common Subsequence (LCS).mp4
15 MB
10 Metrics For Language/006 Q&A Performance With ROUGE.mp4
19 MB
10 Metrics For Language/external-assets-links.txt
680 B
11 Reader-Retriever QA With Haystack/001 Intro to Retriever-Reader and Haystack.mp4
14 MB
11 Reader-Retriever QA With Haystack/002 What is Elasticsearch_.mp4
24 MB
11 Reader-Retriever QA With Haystack/003 Elasticsearch Setup (Windows).mp4
21 MB
11 Reader-Retriever QA With Haystack/004 Elasticsearch Setup (Linux).mp4
20 MB
11 Reader-Retriever QA With Haystack/005 Elasticsearch in Haystack.mp4
39 MB
11 Reader-Retriever QA With Haystack/006 Sparse Retrievers.mp4
20 MB
11 Reader-Retriever QA With Haystack/007 Cleaning the Index.mp4
26 MB
11 Reader-Retriever QA With Haystack/008 Implementing a BM25 Retriever.mp4
12 MB
11 Reader-Retriever QA With Haystack/009 What is FAISS_.mp4
43 MB
11 Reader-Retriever QA With Haystack/010 FAISS in Haystack.mp4
68 MB
11 Reader-Retriever QA With Haystack/011 What is DPR_.mp4
30 MB
11 Reader-Retriever QA With Haystack/012 The DPR Architecture.mp4
14 MB
11 Reader-Retriever QA With Haystack/013 Retriever-Reader Stack.mp4
75 MB
11 Reader-Retriever QA With Haystack/external-assets-links.txt
1.8 kB
12 [Project] Open-Domain QA/001 ODQA Stack Structure.mp4
6.2 MB
12 [Project] Open-Domain QA/002 Creating the Database.mp4
42 MB
12 [Project] Open-Domain QA/003 Building the Haystack Pipeline.mp4
56 MB
12 [Project] Open-Domain QA/external-assets-links.txt
366 B
13 Similarity/001 Introduction to Similarity.mp4
28 MB
13 Similarity/002 Extracting The Last Hidden State Tensor.mp4
30 MB
13 Similarity/003 Sentence Vectors With Mean Pooling.mp4
32 MB
13 Similarity/004 Using Cosine Similarity.mp4
34 MB
13 Similarity/005 Similarity With Sentence-Transformers.mp4
23 MB
14 Fine-Tuning Transformer Models/001 Visual Guide to BERT Pretraining.mp4
29 MB
14 Fine-Tuning Transformer Models/002 Introduction to BERT For Pretraining Code.mp4
29 MB
14 Fine-Tuning Transformer Models/003 BERT Pretraining - Masked-Language Modeling (MLM).mp4
47 MB
14 Fine-Tuning Transformer Models/004 BERT Pretraining - Next Sentence Prediction (NSP).mp4
42 MB
14 Fine-Tuning Transformer Models/005 The Logic of MLM.mp4
79 MB
14 Fine-Tuning Transformer Models/006 Fine-tuning with MLM - Data Preparation.mp4
77 MB
14 Fine-Tuning Transformer Models/007 Fine-tuning with MLM - Training.mp4
70 MB
14 Fine-Tuning Transformer Models/008 Fine-tuning with MLM - Training with Trainer.mp4
20 MB
14 Fine-Tuning Transformer Models/009 The Logic of NSP.mp4
21 MB
14 Fine-Tuning Transformer Models/010 Fine-tuning with NSP - Data Preparation.mp4
78 MB
14 Fine-Tuning Transformer Models/011 Fine-tuning with NSP - DataLoader.mp4
14 MB
14 Fine-Tuning Transformer Models/012 The Logic of MLM and NSP.mp4
26 MB
14 Fine-Tuning Transformer Models/013 Fine-tuning with MLM and NSP - Data Preparation.mp4
44 MB
14 Fine-Tuning Transformer Models/external-assets-links.txt
1.3 kB