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[Udemy] Natural Language Processing With Transformers in Python (06.2021)
大小 3.29 GB
文件数 288
Info Hash: 15A0A25219359A8870CB3F3844C0E975A3826772
收录时间 2026-02-14 13:30:15
更新时间 2026-02-14 13:30:15
文件列表 (288)
1. Introduction/1. Introduction.mp4
9.2 MB
1. Introduction/1. Introduction.srt
3.1 KB
1. Introduction/2. Course Overview.mp4
34.38 MB
1. Introduction/2. Course Overview.srt
8.08 KB
1. Introduction/2.1 GitHub Repo.html
103 B
1. Introduction/3. Environment Setup.mp4
37.25 MB
1. Introduction/3. Environment Setup.srt
7.36 KB
1. Introduction/3.1 Installation Instructions.html
129 B
1. Introduction/4. CUDA Setup.mp4
23.73 MB
1. Introduction/4. CUDA Setup.srt
3.54 KB
1. Introduction/4.1 Installation Instructions.html
129 B
10. Metrics For Language/1. Q&A Performance With Exact Match (EM).mp4
18.17 MB
10. Metrics For Language/1. Q&A Performance With Exact Match (EM).srt
5.53 KB
10. Metrics For Language/1.1 Notebook.html
160 B
10. Metrics For Language/2. ROUGE in Python.mp4
21.66 MB
10. Metrics For Language/2. ROUGE in Python.srt
4.47 KB
10. Metrics For Language/2.1 Notebook.html
154 B
10. Metrics For Language/3. Applying ROUGE to Q&A.mp4
33.95 MB
10. Metrics For Language/3. Applying ROUGE to Q&A.srt
8.58 KB
10. Metrics For Language/3.1 Notebook.html
162 B
10. Metrics For Language/4. Recall, Precision and F1.mp4
21.02 MB
10. Metrics For Language/4. Recall, Precision and F1.srt
5.44 KB
10. Metrics For Language/4.1 Notebook.html
154 B
10. Metrics For Language/5. Longest Common Subsequence (LCS).mp4
14.95 MB
10. Metrics For Language/5. Longest Common Subsequence (LCS).srt
3.02 KB
10. Metrics For Language/5.1 Notebook.html
154 B
10. Metrics For Language/6. Q&A Performance With ROUGE.mp4
18.75 MB
10. Metrics For Language/6. Q&A Performance With ROUGE.srt
4.14 KB
10. Metrics For Language/6.1 Notebook.html
154 B
11. Reader-Retriever QA With Haystack/1. Intro to Retriever-Reader and Haystack.mp4
13.94 MB
11. Reader-Retriever QA With Haystack/1. Intro to Retriever-Reader and Haystack.srt
3.8 KB
11. Reader-Retriever QA With Haystack/1.1 Notebook.html
157 B
11. Reader-Retriever QA With Haystack/10. FAISS in Haystack.mp4
68.09 MB
11. Reader-Retriever QA With Haystack/10. FAISS in Haystack.srt
13.35 KB
11. Reader-Retriever QA With Haystack/10.1 Notebook.html
166 B
11. Reader-Retriever QA With Haystack/11. What is DPR.mp4
29.65 MB
11. Reader-Retriever QA With Haystack/11. What is DPR.srt
8.49 KB
11. Reader-Retriever QA With Haystack/11.1 Article.html
189 B
11. Reader-Retriever QA With Haystack/11.2 Notebook.html
160 B
11. Reader-Retriever QA With Haystack/12. The DPR Architecture.mp4
14.28 MB
11. Reader-Retriever QA With Haystack/12. The DPR Architecture.srt
2.25 KB
11. Reader-Retriever QA With Haystack/12.1 Article.html
189 B
11. Reader-Retriever QA With Haystack/12.2 Notebook.html
160 B
11. Reader-Retriever QA With Haystack/13. Retriever-Reader Stack.mp4
75.25 MB
11. Reader-Retriever QA With Haystack/13. Retriever-Reader Stack.srt
11.12 KB
11. Reader-Retriever QA With Haystack/13.1 Notebook.html
155 B
11. Reader-Retriever QA With Haystack/2. What is Elasticsearch.mp4
23.54 MB
11. Reader-Retriever QA With Haystack/2. What is Elasticsearch.srt
7.19 KB
11. Reader-Retriever QA With Haystack/2.1 Elasticsearch (Cloud) Introduction Article.html
195 B
11. Reader-Retriever QA With Haystack/3. Elasticsearch Setup (Windows).mp4
20.9 MB
11. Reader-Retriever QA With Haystack/3. Elasticsearch Setup (Windows).srt
2.08 KB
11. Reader-Retriever QA With Haystack/4. Elasticsearch Setup (Linux).mp4
20.21 MB
11. Reader-Retriever QA With Haystack/4. Elasticsearch Setup (Linux).srt
2.01 KB
11. Reader-Retriever QA With Haystack/5. Elasticsearch in Haystack.mp4
39.02 MB
11. Reader-Retriever QA With Haystack/5. Elasticsearch in Haystack.srt
8.69 KB
11. Reader-Retriever QA With Haystack/5.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/6. Sparse Retrievers.mp4
20.37 MB
11. Reader-Retriever QA With Haystack/6. Sparse Retrievers.srt
4.18 KB
11. Reader-Retriever QA With Haystack/6.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/7. Cleaning the Index.mp4
26.45 MB
11. Reader-Retriever QA With Haystack/7. Cleaning the Index.srt
5.23 KB
11. Reader-Retriever QA With Haystack/7.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/8. Implementing a BM25 Retriever.mp4
12.55 MB
11. Reader-Retriever QA With Haystack/8. Implementing a BM25 Retriever.srt
2.49 KB
11. Reader-Retriever QA With Haystack/8.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/9. What is FAISS.mp4
42.9 MB
11. Reader-Retriever QA With Haystack/9. What is FAISS.srt
9.85 KB
11. Reader-Retriever QA With Haystack/9.1 Article.html
170 B
11. Reader-Retriever QA With Haystack/9.2 Notebook.html
162 B
12. [Project] Open-Domain QA/1. ODQA Stack Structure.mp4
6.23 MB
12. [Project] Open-Domain QA/1. ODQA Stack Structure.srt
1.97 KB
12. [Project] Open-Domain QA/2. Creating the Database.mp4
42.43 MB
12. [Project] Open-Domain QA/2. Creating the Database.srt
7.73 KB
12. [Project] Open-Domain QA/2.1 Data.html
145 B
12. [Project] Open-Domain QA/2.2 Notebook.html
174 B
12. [Project] Open-Domain QA/3. Building the Haystack Pipeline.mp4
55.8 MB
12. [Project] Open-Domain QA/3. Building the Haystack Pipeline.srt
8.96 KB
12. [Project] Open-Domain QA/3.1 Notebook.html
180 B
13. Similarity/1. Introduction to Similarity.mp4
28.25 MB
13. Similarity/1. Introduction to Similarity.srt
7.85 KB
13. Similarity/2. Extracting The Last Hidden State Tensor.mp4
29.76 MB
13. Similarity/2. Extracting The Last Hidden State Tensor.srt
5.67 KB
13. Similarity/3. Sentence Vectors With Mean Pooling.mp4
32.09 MB
13. Similarity/3. Sentence Vectors With Mean Pooling.srt
8.04 KB
13. Similarity/4. Using Cosine Similarity.mp4
33.86 MB
13. Similarity/4. Using Cosine Similarity.srt
5.83 KB
13. Similarity/5. Similarity With Sentence-Transformers.mp4
23.02 MB
13. Similarity/5. Similarity With Sentence-Transformers.srt
4.13 KB
14. Fine-Tuning Transformer Models/1. Visual Guide to BERT Pretraining.mp4
28.6 MB
14. Fine-Tuning Transformer Models/1. Visual Guide to BERT Pretraining.srt
9.71 KB
14. Fine-Tuning Transformer Models/10. Fine-tuning with NSP - Data Preparation.mp4
77.97 MB
14. Fine-Tuning Transformer Models/10. Fine-tuning with NSP - Data Preparation.srt
14.65 KB
14. Fine-Tuning Transformer Models/10.1 Notebook.html
151 B
14. Fine-Tuning Transformer Models/11. Fine-tuning with NSP - DataLoader.mp4
14.27 MB
14. Fine-Tuning Transformer Models/11. Fine-tuning with NSP - DataLoader.srt
3.34 KB
14. Fine-Tuning Transformer Models/11.1 Notebook.html
151 B
14. Fine-Tuning Transformer Models/12. Setup the NSP Fine-tuning Training Loop.html
136 B
14. Fine-Tuning Transformer Models/13. The Logic of MLM and NSP.mp4
26.25 MB
14. Fine-Tuning Transformer Models/13. The Logic of MLM and NSP.srt
5.46 KB
14. Fine-Tuning Transformer Models/13.1 Notebook.html
156 B
14. Fine-Tuning Transformer Models/14. Fine-tuning with MLM and NSP - Data Preparation.mp4
43.62 MB
14. Fine-Tuning Transformer Models/14. Fine-tuning with MLM and NSP - Data Preparation.srt
8.94 KB
14. Fine-Tuning Transformer Models/14.1 Notebook.html
159 B
14. Fine-Tuning Transformer Models/15. Setup DataLoader and Model Fine-tuning For MLM and NSP.html
136 B
14. Fine-Tuning Transformer Models/2. Introduction to BERT For Pretraining Code.mp4
29.26 MB
14. Fine-Tuning Transformer Models/2. Introduction to BERT For Pretraining Code.srt
5.14 KB
14. Fine-Tuning Transformer Models/2.1 Notebook.html
143 B
14. Fine-Tuning Transformer Models/3. BERT Pretraining - Masked-Language Modeling (MLM).mp4
46.71 MB
14. Fine-Tuning Transformer Models/3. BERT Pretraining - Masked-Language Modeling (MLM).srt
9.34 KB
14. Fine-Tuning Transformer Models/3.1 Notebook.html
143 B
14. Fine-Tuning Transformer Models/4. BERT Pretraining - Next Sentence Prediction (NSP).mp4
42.08 MB
14. Fine-Tuning Transformer Models/4. BERT Pretraining - Next Sentence Prediction (NSP).srt
6.98 KB
14. Fine-Tuning Transformer Models/4.1 Notebook.html
143 B
14. Fine-Tuning Transformer Models/5. The Logic of MLM.mp4
79.41 MB
14. Fine-Tuning Transformer Models/5. The Logic of MLM.srt
13.33 KB
14. Fine-Tuning Transformer Models/5.1 Notebook.html
154 B
14. Fine-Tuning Transformer Models/6. Fine-tuning with MLM - Data Preparation.mp4
76.72 MB
14. Fine-Tuning Transformer Models/6. Fine-tuning with MLM - Data Preparation.srt
13.44 KB
14. Fine-Tuning Transformer Models/6.1 Notebook.html
151 B
14. Fine-Tuning Transformer Models/7. Fine-tuning with MLM - Training.mp4
69.69 MB
14. Fine-Tuning Transformer Models/7. Fine-tuning with MLM - Training.srt
13.67 KB
14. Fine-Tuning Transformer Models/7.1 Notebook.html
151 B
14. Fine-Tuning Transformer Models/8. Fine-tuning with MLM - Training with Trainer.mp4
19.88 MB
14. Fine-Tuning Transformer Models/8. Fine-tuning with MLM - Training with Trainer.srt
3.37 KB
14. Fine-Tuning Transformer Models/8.1 Notebook.html
159 B
14. Fine-Tuning Transformer Models/9. The Logic of NSP.mp4
20.88 MB
14. Fine-Tuning Transformer Models/9. The Logic of NSP.srt
4.61 KB
14. Fine-Tuning Transformer Models/9.1 Notebook.html
154 B
2. NLP and Transformers/1. The Three Eras of AI.mp4
22.2 MB
2. NLP and Transformers/1. The Three Eras of AI.srt
7.72 KB
2. NLP and Transformers/10. Transformer Heads.mp4
39.82 MB
2. NLP and Transformers/10. Transformer Heads.srt
10.67 KB
2. NLP and Transformers/2. Pros and Cons of Neural AI.mp4
32.79 MB
2. NLP and Transformers/2. Pros and Cons of Neural AI.srt
5.43 KB
2. NLP and Transformers/2.1 2010 Flash Crash.html
159 B
2. NLP and Transformers/2.2 Amazon AI Recruitment Bias.html
144 B
2. NLP and Transformers/2.3 Self-Driving Limitations.html
163 B
2. NLP and Transformers/3. Word Vectors.mp4
21.73 MB
2. NLP and Transformers/3. Word Vectors.srt
5.1 KB
2. NLP and Transformers/4. Recurrent Neural Networks.mp4
17.1 MB
2. NLP and Transformers/4. Recurrent Neural Networks.srt
4.47 KB
2. NLP and Transformers/5. Long Short-Term Memory.mp4
6.34 MB
2. NLP and Transformers/5. Long Short-Term Memory.srt
2.18 KB
2. NLP and Transformers/6. Encoder-Decoder Attention.mp4
25.17 MB
2. NLP and Transformers/6. Encoder-Decoder Attention.srt
6.06 KB
2. NLP and Transformers/7. Self-Attention.mp4
20.8 MB
2. NLP and Transformers/7. Self-Attention.srt
4.63 KB
2. NLP and Transformers/8. Multi-head Attention.mp4
13.33 MB
2. NLP and Transformers/8. Multi-head Attention.srt
3.21 KB
2. NLP and Transformers/9. Positional Encoding.mp4
55.53 MB
2. NLP and Transformers/9. Positional Encoding.srt
9.62 KB
3. Preprocessing for NLP/1. Stopwords.mp4
23.06 MB
3. Preprocessing for NLP/1. Stopwords.srt
6.26 KB
3. Preprocessing for NLP/1.1 Notebook.html
153 B
3. Preprocessing for NLP/2. Tokens Introduction.mp4
24.04 MB
3. Preprocessing for NLP/2. Tokens Introduction.srt
8.43 KB
3. Preprocessing for NLP/2.1 Notebook.html
150 B
3. Preprocessing for NLP/3. Model-Specific Special Tokens.mp4
18.89 MB
3. Preprocessing for NLP/3. Model-Specific Special Tokens.srt
7.11 KB
3. Preprocessing for NLP/3.1 Notebook.html
150 B
3. Preprocessing for NLP/4. Stemming.mp4
17.24 MB
3. Preprocessing for NLP/4. Stemming.srt
6.46 KB
3. Preprocessing for NLP/4.1 Notebook.html
152 B
3. Preprocessing for NLP/5. Lemmatization.mp4
10.58 MB
3. Preprocessing for NLP/5. Lemmatization.srt
4.23 KB
3. Preprocessing for NLP/5.1 Notebook.html
157 B
3. Preprocessing for NLP/6. Unicode Normalization - Canonical and Compatibility Equivalence.mp4
16.97 MB
3. Preprocessing for NLP/6. Unicode Normalization - Canonical and Compatibility Equivalence.srt
6.5 KB
3. Preprocessing for NLP/6.1 Notebook.html
157 B
3. Preprocessing for NLP/7. Unicode Normalization - Composition and Decomposition.mp4
20.25 MB
3. Preprocessing for NLP/7. Unicode Normalization - Composition and Decomposition.srt
5.67 KB
3. Preprocessing for NLP/7.1 Notebook.html
157 B
3. Preprocessing for NLP/8. Unicode Normalization - NFD and NFC.mp4
20.02 MB
3. Preprocessing for NLP/8. Unicode Normalization - NFD and NFC.srt
6.23 KB
3. Preprocessing for NLP/8.1 Notebook.html
157 B
3. Preprocessing for NLP/9. Unicode Normalization - NFKD and NFKC.mp4
30.42 MB
3. Preprocessing for NLP/9. Unicode Normalization - NFKD and NFKC.srt
8.68 KB
3. Preprocessing for NLP/9.1 Notebook.html
157 B
4. Attention/1. Attention Introduction.mp4
15.79 MB
4. Attention/1. Attention Introduction.srt
2.7 KB
4. Attention/1.1 Notebook.html
147 B
4. Attention/2. Alignment With Dot-Product.mp4
49.12 MB
4. Attention/2. Alignment With Dot-Product.srt
13.75 KB
4. Attention/2.1 Notebook.html
161 B
4. Attention/3. Dot-Product Attention.mp4
28.99 MB
4. Attention/3. Dot-Product Attention.srt
5.51 KB
4. Attention/3.1 Notebook.html
161 B
4. Attention/4. Self Attention.mp4
28.4 MB
4. Attention/4. Self Attention.srt
6.23 KB
4. Attention/4.1 Notebook.html
154 B
4. Attention/5. Bidirectional Attention.mp4
10.78 MB
4. Attention/5. Bidirectional Attention.srt
2.95 KB
4. Attention/5.1 Notebook.html
163 B
4. Attention/6. Multi-head and Scaled Dot-Product Attention.mp4
33.83 MB
4. Attention/6. Multi-head and Scaled Dot-Product Attention.srt
7.12 KB
4. Attention/6.1 Notebook.html
159 B
5. Language Classification/1. Introduction to Sentiment Analysis.mp4
37.53 MB
5. Language Classification/1. Introduction to Sentiment Analysis.srt
10.08 KB
5. Language Classification/1.1 Notebook.html
178 B
5. Language Classification/2. Prebuilt Flair Models.mp4
30.71 MB
5. Language Classification/2. Prebuilt Flair Models.srt
9.35 KB
5. Language Classification/2.1 Notebook.html
174 B
5. Language Classification/3. Introduction to Sentiment Models With Transformers.mp4
26.92 MB
5. Language Classification/3. Introduction to Sentiment Models With Transformers.srt
7.09 KB
5. Language Classification/3.1 Notebook.html
181 B
5. Language Classification/4. Tokenization And Special Tokens For BERT.mp4
55.43 MB
5. Language Classification/4. Tokenization And Special Tokens For BERT.srt
8.41 KB
5. Language Classification/4.1 Notebook.html
181 B
5. Language Classification/5. Making Predictions.mp4
25.97 MB
5. Language Classification/5. Making Predictions.srt
6.86 KB
5. Language Classification/5.1 Notebook.html
181 B
6. [Project] Sentiment Model With TensorFlow and Transformers/1. Project Overview.mp4
12.51 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/1. Project Overview.srt
3.39 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/2. Getting the Data (Kaggle API).mp4
35.02 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/2. Getting the Data (Kaggle API).srt
8.39 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/2.1 Notebook.html
176 B
6. [Project] Sentiment Model With TensorFlow and Transformers/3. Preprocessing.mp4
62.49 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/3. Preprocessing.srt
15.17 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/3.1 Notebook.html
176 B
6. [Project] Sentiment Model With TensorFlow and Transformers/4. Building a Dataset.mp4
22.57 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/4. Building a Dataset.srt
6.05 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/4.1 Notebook.html
177 B
6. [Project] Sentiment Model With TensorFlow and Transformers/5. Dataset Shuffle, Batch, Split, and Save.mp4
30.17 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/5. Dataset Shuffle, Batch, Split, and Save.srt
7.65 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/5.1 Notebook.html
177 B
6. [Project] Sentiment Model With TensorFlow and Transformers/6. Build and Save.mp4
77.01 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/6. Build and Save.srt
14.07 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/6.1 Notebook.html
178 B
6. [Project] Sentiment Model With TensorFlow and Transformers/7. Loading and Prediction.mp4
56.77 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/7. Loading and Prediction.srt
11.68 KB
6. [Project] Sentiment Model With TensorFlow and Transformers/7.1 Notebook.html
179 B
7. Long Text Classification With BERT/1. Classification of Long Text Using Windows.mp4
116.14 MB
7. Long Text Classification With BERT/1. Classification of Long Text Using Windows.srt
24.21 KB
7. Long Text Classification With BERT/1.1 Article.html
188 B
7. Long Text Classification With BERT/1.2 Notebook.html
173 B
7. Long Text Classification With BERT/2. Window Method in PyTorch.mp4
84.94 MB
7. Long Text Classification With BERT/2. Window Method in PyTorch.srt
16.33 KB
7. Long Text Classification With BERT/2.1 Notebook.html
178 B
8. Named Entity Recognition (NER)/1. Introduction to spaCy.mp4
51.64 MB
8. Named Entity Recognition (NER)/1. Introduction to spaCy.srt
9.38 KB
8. Named Entity Recognition (NER)/1.1 Notebook.html
169 B
8. Named Entity Recognition (NER)/1.2 spaCy Model Docs.html
84 B
8. Named Entity Recognition (NER)/10. NER With roBERTa.mp4
59.01 MB
8. Named Entity Recognition (NER)/10. NER With roBERTa.srt
10.38 KB
8. Named Entity Recognition (NER)/10.1 Notebook.html
177 B
8. Named Entity Recognition (NER)/2. Extracting Entities.mp4
33.53 MB
8. Named Entity Recognition (NER)/2. Extracting Entities.srt
6.74 KB
8. Named Entity Recognition (NER)/2.1 Notebook.html
169 B
8. Named Entity Recognition (NER)/3. NER Walkthrough.html
136 B
8. Named Entity Recognition (NER)/4. Authenticating With The Reddit API.mp4
35.63 MB
8. Named Entity Recognition (NER)/4. Authenticating With The Reddit API.srt
7.82 KB
8. Named Entity Recognition (NER)/4.1 Notebook.html
174 B
8. Named Entity Recognition (NER)/5. Pulling Data With The Reddit API.mp4
88.96 MB
8. Named Entity Recognition (NER)/5. Pulling Data With The Reddit API.srt
12.92 KB
8. Named Entity Recognition (NER)/5.1 Notebook.html
174 B
8. Named Entity Recognition (NER)/6. Extracting ORGs From Reddit Data.mp4
28.11 MB
8. Named Entity Recognition (NER)/6. Extracting ORGs From Reddit Data.srt
6.7 KB
8. Named Entity Recognition (NER)/6.1 Data.html
171 B
8. Named Entity Recognition (NER)/6.2 Notebook.html
176 B
8. Named Entity Recognition (NER)/7. Getting Entity Frequency.mp4
18.39 MB
8. Named Entity Recognition (NER)/7. Getting Entity Frequency.srt
3.92 KB
8. Named Entity Recognition (NER)/7.1 Notebook.html
176 B
8. Named Entity Recognition (NER)/8. Entity Blacklist.mp4
20.15 MB
8. Named Entity Recognition (NER)/8. Entity Blacklist.srt
3.98 KB
8. Named Entity Recognition (NER)/8.1 Notebook.html
176 B
8. Named Entity Recognition (NER)/9. NER With Sentiment.mp4
99.88 MB
8. Named Entity Recognition (NER)/9. NER With Sentiment.srt
19.6 KB
8. Named Entity Recognition (NER)/9.1 Notebook.html
172 B
9. Question and Answering/1. Open Domain and Reading Comprehension.mp4
16.07 MB
9. Question and Answering/1. Open Domain and Reading Comprehension.srt
3.56 KB
9. Question and Answering/1.1 Notebook.html
160 B
9. Question and Answering/2. Retrievers, Readers, and Generators.mp4
28.68 MB
9. Question and Answering/2. Retrievers, Readers, and Generators.srt
7.08 KB
9. Question and Answering/2.1 Notebook.html
160 B
9. Question and Answering/3. Intro to SQuAD 2.0.mp4
25.39 MB
9. Question and Answering/3. Intro to SQuAD 2.0.srt
6.65 KB
9. Question and Answering/3.1 Notebook.html
162 B
9. Question and Answering/4. Processing SQuAD Training Data.mp4
38.42 MB
9. Question and Answering/4. Processing SQuAD Training Data.srt
7.04 KB
9. Question and Answering/4.1 Notebook.html
175 B
9. Question and Answering/5. (Optional) Processing SQuAD Training Data with Match-Case.mp4
30.1 MB
9. Question and Answering/5. (Optional) Processing SQuAD Training Data with Match-Case.srt
5.06 KB
9. Question and Answering/5.1 Notebook.html
167 B
9. Question and Answering/5.2 Pattern Matching Article.html
184 B
9. Question and Answering/6. Processing SQuAD Dev Data.html
136 B
9. Question and Answering/7. Our First Q&A Model.mp4
45.71 MB
9. Question and Answering/7. Our First Q&A Model.srt
9.03 KB
9. Question and Answering/7.1 Notebook.html
163 B
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