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[Udemy] Natural Language Processing With Transformers in Python (06.2021)

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File Name
Size
1. Introduction/1. Introduction.mp4
9.2 MB
1. Introduction/1. Introduction.srt
3.1 kB
1. Introduction/2. Course Overview.mp4
34 MB
1. Introduction/2. Course Overview.srt
8.1 kB
1. Introduction/2.1 GitHub Repo.html
103 B
1. Introduction/3. Environment Setup.mp4
37 MB
1. Introduction/3. Environment Setup.srt
7.4 kB
1. Introduction/3.1 Installation Instructions.html
129 B
1. Introduction/4. CUDA Setup.mp4
24 MB
1. Introduction/4. CUDA Setup.srt
3.5 kB
1. Introduction/4.1 Installation Instructions.html
129 B
10. Metrics For Language/1. Q&A Performance With Exact Match (EM).mp4
18 MB
10. Metrics For Language/1. Q&A Performance With Exact Match (EM).srt
5.5 kB
10. Metrics For Language/1.1 Notebook.html
160 B
10. Metrics For Language/2. ROUGE in Python.mp4
22 MB
10. Metrics For Language/2. ROUGE in Python.srt
4.5 kB
10. Metrics For Language/2.1 Notebook.html
154 B
10. Metrics For Language/3. Applying ROUGE to Q&A.mp4
34 MB
10. Metrics For Language/3. Applying ROUGE to Q&A.srt
8.6 kB
10. Metrics For Language/3.1 Notebook.html
162 B
10. Metrics For Language/4. Recall, Precision and F1.mp4
21 MB
10. Metrics For Language/4. Recall, Precision and F1.srt
5.4 kB
10. Metrics For Language/4.1 Notebook.html
154 B
10. Metrics For Language/5. Longest Common Subsequence (LCS).mp4
15 MB
10. Metrics For Language/5. Longest Common Subsequence (LCS).srt
3.0 kB
10. Metrics For Language/5.1 Notebook.html
154 B
10. Metrics For Language/6. Q&A Performance With ROUGE.mp4
19 MB
10. Metrics For Language/6. Q&A Performance With ROUGE.srt
4.1 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
14 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 MB
11. Reader-Retriever QA With Haystack/10. FAISS in Haystack.srt
13 kB
11. Reader-Retriever QA With Haystack/10.1 Notebook.html
166 B
11. Reader-Retriever QA With Haystack/11. What is DPR.mp4
30 MB
11. Reader-Retriever QA With Haystack/11. What is DPR.srt
8.5 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 MB
11. Reader-Retriever QA With Haystack/12. The DPR Architecture.srt
2.2 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 MB
11. Reader-Retriever QA With Haystack/13. Retriever-Reader Stack.srt
11 kB
11. Reader-Retriever QA With Haystack/13.1 Notebook.html
155 B
11. Reader-Retriever QA With Haystack/2. What is Elasticsearch.mp4
24 MB
11. Reader-Retriever QA With Haystack/2. What is Elasticsearch.srt
7.2 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
21 MB
11. Reader-Retriever QA With Haystack/3. Elasticsearch Setup (Windows).srt
2.1 kB
11. Reader-Retriever QA With Haystack/4. Elasticsearch Setup (Linux).mp4
20 MB
11. Reader-Retriever QA With Haystack/4. Elasticsearch Setup (Linux).srt
2.0 kB
11. Reader-Retriever QA With Haystack/5. Elasticsearch in Haystack.mp4
39 MB
11. Reader-Retriever QA With Haystack/5. Elasticsearch in Haystack.srt
8.7 kB
11. Reader-Retriever QA With Haystack/5.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/6. Sparse Retrievers.mp4
20 MB
11. Reader-Retriever QA With Haystack/6. Sparse Retrievers.srt
4.2 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 MB
11. Reader-Retriever QA With Haystack/7. Cleaning the Index.srt
5.2 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
13 MB
11. Reader-Retriever QA With Haystack/8. Implementing a BM25 Retriever.srt
2.5 kB
11. Reader-Retriever QA With Haystack/8.1 Notebook.html
168 B
11. Reader-Retriever QA With Haystack/9. What is FAISS.mp4
43 MB
11. Reader-Retriever QA With Haystack/9. What is FAISS.srt
9.9 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
6.2 MB
12. [Project] Open-Domain QA/1. ODQA Stack Structure.srt
2.0 kB
12. [Project] Open-Domain QA/2. Creating the Database.mp4
42 MB
12. [Project] Open-Domain QA/2. Creating the Database.srt
7.7 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
56 MB
12. [Project] Open-Domain QA/3. Building the Haystack Pipeline.srt
9.0 kB
12. [Project] Open-Domain QA/3.1 Notebook.html
180 B
13. Similarity/1. Introduction to Similarity.mp4
28 MB
13. Similarity/1. Introduction to Similarity.srt
7.9 kB
13. Similarity/2. Extracting The Last Hidden State Tensor.mp4
30 MB
13. Similarity/2. Extracting The Last Hidden State Tensor.srt
5.7 kB
13. Similarity/3. Sentence Vectors With Mean Pooling.mp4
32 MB
13. Similarity/3. Sentence Vectors With Mean Pooling.srt
8.0 kB
13. Similarity/4. Using Cosine Similarity.mp4
34 MB
13. Similarity/4. Using Cosine Similarity.srt
5.8 kB
13. Similarity/5. Similarity With Sentence-Transformers.mp4
23 MB
13. Similarity/5. Similarity With Sentence-Transformers.srt
4.1 kB
14. Fine-Tuning Transformer Models/1. Visual Guide to BERT Pretraining.mp4
29 MB
14. Fine-Tuning Transformer Models/1. Visual Guide to BERT Pretraining.srt
9.7 kB
14. Fine-Tuning Transformer Models/10. Fine-tuning with NSP - Data Preparation.mp4
78 MB
14. Fine-Tuning Transformer Models/10. Fine-tuning with NSP - Data Preparation.srt
15 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 MB
14. Fine-Tuning Transformer Models/11. Fine-tuning with NSP - DataLoader.srt
3.3 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 MB
14. Fine-Tuning Transformer Models/13. The Logic of MLM and NSP.srt
5.5 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
44 MB
14. Fine-Tuning Transformer Models/14. Fine-tuning with MLM and NSP - Data Preparation.srt
8.9 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 MB
14. Fine-Tuning Transformer Models/2. Introduction to BERT For Pretraining Code.srt
5.1 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
47 MB
14. Fine-Tuning Transformer Models/3. BERT Pretraining - Masked-Language Modeling (MLM).srt
9.3 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 MB
14. Fine-Tuning Transformer Models/4. BERT Pretraining - Next Sentence Prediction (NSP).srt
7.0 kB
14. Fine-Tuning Transformer Models/4.1 Notebook.html
143 B
14. Fine-Tuning Transformer Models/5. The Logic of MLM.mp4
79 MB
14. Fine-Tuning Transformer Models/5. The Logic of MLM.srt
13 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
77 MB
14. Fine-Tuning Transformer Models/6. Fine-tuning with MLM - Data Preparation.srt
13 kB
14. Fine-Tuning Transformer Models/6.1 Notebook.html
151 B
14. Fine-Tuning Transformer Models/7. Fine-tuning with MLM - Training.mp4
70 MB
14. Fine-Tuning Transformer Models/7. Fine-tuning with MLM - Training.srt
14 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
20 MB
14. Fine-Tuning Transformer Models/8. Fine-tuning with MLM - Training with Trainer.srt
3.4 kB
14. Fine-Tuning Transformer Models/8.1 Notebook.html
159 B
14. Fine-Tuning Transformer Models/9. The Logic of NSP.mp4
21 MB
14. Fine-Tuning Transformer Models/9. The Logic of NSP.srt
4.6 kB
14. Fine-Tuning Transformer Models/9.1 Notebook.html
154 B
2. NLP and Transformers/1. The Three Eras of AI.mp4
22 MB
2. NLP and Transformers/1. The Three Eras of AI.srt
7.7 kB
2. NLP and Transformers/10. Transformer Heads.mp4
40 MB
2. NLP and Transformers/10. Transformer Heads.srt
11 kB
2. NLP and Transformers/2. Pros and Cons of Neural AI.mp4
33 MB
2. NLP and Transformers/2. Pros and Cons of Neural AI.srt
5.4 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
22 MB
2. NLP and Transformers/3. Word Vectors.srt
5.1 kB
2. NLP and Transformers/4. Recurrent Neural Networks.mp4
17 MB
2. NLP and Transformers/4. Recurrent Neural Networks.srt
4.5 kB
2. NLP and Transformers/5. Long Short-Term Memory.mp4
6.3 MB
2. NLP and Transformers/5. Long Short-Term Memory.srt
2.2 kB
2. NLP and Transformers/6. Encoder-Decoder Attention.mp4
25 MB
2. NLP and Transformers/6. Encoder-Decoder Attention.srt
6.1 kB
2. NLP and Transformers/7. Self-Attention.mp4
21 MB
2. NLP and Transformers/7. Self-Attention.srt
4.6 kB
2. NLP and Transformers/8. Multi-head Attention.mp4
13 MB
2. NLP and Transformers/8. Multi-head Attention.srt
3.2 kB
2. NLP and Transformers/9. Positional Encoding.mp4
56 MB
2. NLP and Transformers/9. Positional Encoding.srt
9.6 kB
3. Preprocessing for NLP/1. Stopwords.mp4
23 MB
3. Preprocessing for NLP/1. Stopwords.srt
6.3 kB
3. Preprocessing for NLP/1.1 Notebook.html
153 B
3. Preprocessing for NLP/2. Tokens Introduction.mp4
24 MB
3. Preprocessing for NLP/2. Tokens Introduction.srt
8.4 kB
3. Preprocessing for NLP/2.1 Notebook.html
150 B
3. Preprocessing for NLP/3. Model-Specific Special Tokens.mp4
19 MB
3. Preprocessing for NLP/3. Model-Specific Special Tokens.srt
7.1 kB
3. Preprocessing for NLP/3.1 Notebook.html
150 B
3. Preprocessing for NLP/4. Stemming.mp4
17 MB
3. Preprocessing for NLP/4. Stemming.srt
6.5 kB
3. Preprocessing for NLP/4.1 Notebook.html
152 B
3. Preprocessing for NLP/5. Lemmatization.mp4
11 MB
3. Preprocessing for NLP/5. Lemmatization.srt
4.2 kB
3. Preprocessing for NLP/5.1 Notebook.html
157 B
3. Preprocessing for NLP/6. Unicode Normalization - Canonical and Compatibility Equivalence.mp4
17 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 MB
3. Preprocessing for NLP/7. Unicode Normalization - Composition and Decomposition.srt
5.7 kB
3. Preprocessing for NLP/7.1 Notebook.html
157 B
3. Preprocessing for NLP/8. Unicode Normalization - NFD and NFC.mp4
20 MB
3. Preprocessing for NLP/8. Unicode Normalization - NFD and NFC.srt
6.2 kB
3. Preprocessing for NLP/8.1 Notebook.html
157 B
3. Preprocessing for NLP/9. Unicode Normalization - NFKD and NFKC.mp4
30 MB
3. Preprocessing for NLP/9. Unicode Normalization - NFKD and NFKC.srt
8.7 kB
3. Preprocessing for NLP/9.1 Notebook.html
157 B
4. Attention/1. Attention Introduction.mp4
16 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 MB
4. Attention/2. Alignment With Dot-Product.srt
14 kB
4. Attention/2.1 Notebook.html
161 B
4. Attention/3. Dot-Product Attention.mp4
29 MB
4. Attention/3. Dot-Product Attention.srt
5.5 kB
4. Attention/3.1 Notebook.html
161 B
4. Attention/4. Self Attention.mp4
28 MB
4. Attention/4. Self Attention.srt
6.2 kB
4. Attention/4.1 Notebook.html
154 B
4. Attention/5. Bidirectional Attention.mp4
11 MB
4. Attention/5. Bidirectional Attention.srt
3.0 kB
4. Attention/5.1 Notebook.html
163 B
4. Attention/6. Multi-head and Scaled Dot-Product Attention.mp4
34 MB
4. Attention/6. Multi-head and Scaled Dot-Product Attention.srt
7.1 kB
4. Attention/6.1 Notebook.html
159 B
5. Language Classification/1. Introduction to Sentiment Analysis.mp4
38 MB
5. Language Classification/1. Introduction to Sentiment Analysis.srt
10 kB
5. Language Classification/1.1 Notebook.html
178 B
5. Language Classification/2. Prebuilt Flair Models.mp4
31 MB
5. Language Classification/2. Prebuilt Flair Models.srt
9.3 kB
5. Language Classification/2.1 Notebook.html
174 B
5. Language Classification/3. Introduction to Sentiment Models With Transformers.mp4
27 MB
5. Language Classification/3. Introduction to Sentiment Models With Transformers.srt
7.1 kB
5. Language Classification/3.1 Notebook.html
181 B
5. Language Classification/4. Tokenization And Special Tokens For BERT.mp4
55 MB
5. Language Classification/4. Tokenization And Special Tokens For BERT.srt
8.4 kB
5. Language Classification/4.1 Notebook.html
181 B
5. Language Classification/5. Making Predictions.mp4
26 MB
5. Language Classification/5. Making Predictions.srt
6.9 kB
5. Language Classification/5.1 Notebook.html
181 B
6. [Project] Sentiment Model With TensorFlow and Transformers/1. Project Overview.mp4
12 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/1. Project Overview.srt
3.4 kB
6. [Project] Sentiment Model With TensorFlow and Transformers/2. Getting the Data (Kaggle API).mp4
35 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/2. Getting the Data (Kaggle API).srt
8.4 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 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/3. Preprocessing.srt
15 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
23 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/4. Building a Dataset.srt
6.0 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 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/5. Dataset Shuffle, Batch, Split, and Save.srt
7.6 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 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/6. Build and Save.srt
14 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
57 MB
6. [Project] Sentiment Model With TensorFlow and Transformers/7. Loading and Prediction.srt
12 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 MB
7. Long Text Classification With BERT/1. Classification of Long Text Using Windows.srt
24 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
85 MB
7. Long Text Classification With BERT/2. Window Method in PyTorch.srt
16 kB
7. Long Text Classification With BERT/2.1 Notebook.html
178 B
8. Named Entity Recognition (NER)/1. Introduction to spaCy.mp4
52 MB
8. Named Entity Recognition (NER)/1. Introduction to spaCy.srt
9.4 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 MB
8. Named Entity Recognition (NER)/10. NER With roBERTa.srt
10 kB
8. Named Entity Recognition (NER)/10.1 Notebook.html
177 B
8. Named Entity Recognition (NER)/2. Extracting Entities.mp4
34 MB
8. Named Entity Recognition (NER)/2. Extracting Entities.srt
6.7 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
36 MB
8. Named Entity Recognition (NER)/4. Authenticating With The Reddit API.srt
7.8 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
89 MB
8. Named Entity Recognition (NER)/5. Pulling Data With The Reddit API.srt
13 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 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 MB
8. Named Entity Recognition (NER)/7. Getting Entity Frequency.srt
3.9 kB
8. Named Entity Recognition (NER)/7.1 Notebook.html
176 B
8. Named Entity Recognition (NER)/8. Entity Blacklist.mp4
20 MB
8. Named Entity Recognition (NER)/8. Entity Blacklist.srt
4.0 kB
8. Named Entity Recognition (NER)/8.1 Notebook.html
176 B
8. Named Entity Recognition (NER)/9. NER With Sentiment.mp4
100 MB
8. Named Entity Recognition (NER)/9. NER With Sentiment.srt
20 kB
8. Named Entity Recognition (NER)/9.1 Notebook.html
172 B
9. Question and Answering/1. Open Domain and Reading Comprehension.mp4
16 MB
9. Question and Answering/1. Open Domain and Reading Comprehension.srt
3.6 kB
9. Question and Answering/1.1 Notebook.html
160 B
9. Question and Answering/2. Retrievers, Readers, and Generators.mp4
29 MB
9. Question and Answering/2. Retrievers, Readers, and Generators.srt
7.1 kB
9. Question and Answering/2.1 Notebook.html
160 B
9. Question and Answering/3. Intro to SQuAD 2.0.mp4
25 MB
9. Question and Answering/3. Intro to SQuAD 2.0.srt
6.7 kB
9. Question and Answering/3.1 Notebook.html
162 B
9. Question and Answering/4. Processing SQuAD Training Data.mp4
38 MB
9. Question and Answering/4. Processing SQuAD Training Data.srt
7.0 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 MB
9. Question and Answering/5. (Optional) Processing SQuAD Training Data with Match-Case.srt
5.1 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
46 MB
9. Question and Answering/7. Our First Q&A Model.srt
9.0 kB
9. Question and Answering/7.1 Notebook.html
163 B