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Checked by:
Category:
Language:
English
Total Size:
5.6 GB
Info Hash:
7B17AF8497B4A3ACFC8DB716958D2C1A567B52CB
Added By:
Added:
Aug. 21, 2023, 4:46 p.m.
Stats:
|
(Last updated: May 20, 2025, 9:28 p.m.)
| File | Size |
|---|---|
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. Introduction.mp4 | 34.6 MB |
| 1. Introduction.srt | 5.6 KB |
| 2. Outline.mp4 | 50.7 MB |
| 2. Outline.srt | 13.5 KB |
| 1. Data Links.html | 256 bytes |
| 1. Anaconda Environment Setup.mp4 | 52.6 MB |
| 1. Anaconda Environment Setup.srt | 20.1 KB |
| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 43.6 MB |
| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt | 15.8 KB |
| 1. How to Code by Yourself (part 1).mp4 | 71.8 MB |
| 1. How to Code by Yourself (part 1).srt | 23.1 KB |
| 2. How to Code by Yourself (part 2).mp4 | 49.1 MB |
| 2. How to Code by Yourself (part 2).srt | 13.2 KB |
| 3. Proof that using Jupyter Notebook is the same as not using it.mp4 | 69.4 MB |
| 3. Proof that using Jupyter Notebook is the same as not using it.srt | 14.9 KB |
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. How to Succeed in this Course (Long Version).mp4 | 17.9 MB |
| 1. How to Succeed in this Course (Long Version).srt | 14.5 KB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 39.0 MB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 32.7 KB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 | 79.7 MB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt | 17.1 KB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 | 108.2 MB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt | 23.9 KB |
| 1. What is the Appendix.mp4 | 16.4 MB |
| 1. What is the Appendix.srt | 3.9 KB |
| 2. BONUS.mp4 | 39.9 MB |
| 2. BONUS.srt | 7.9 KB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 | 43.6 MB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt | 12.0 KB |
| 1.1 Data Links.html | 157 bytes |
| 1.2 Github Link.html | 145 bytes |
| 2. How to use Github & Extra Coding Tips (Optional).mp4 | 63.9 MB |
| 2. How to use Github & Extra Coding Tips (Optional).srt | 15.7 KB |
| 3. Where to get the code, notebooks, and data.mp4 | 17.8 MB |
| 3. Where to get the code, notebooks, and data.srt | 4.3 KB |
| 3.1 Code Link.html | 125 bytes |
| 3.2 Data Links.html | 157 bytes |
| 3.3 Github Link.html | 145 bytes |
| 4. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 | 26.7 MB |
| 4. Are You Beginner, Intermediate, or Advanced All are OK!.srt | 7.1 KB |
| 5. How to Succeed in This Course.mp4 | 41.2 MB |
| 5. How to Succeed in This Course.srt | 13.0 KB |
| 1. Beginner's Corner Section Introduction.mp4 | 49.7 MB |
| 1. Beginner's Corner Section Introduction.srt | 15.1 KB |
| 10. Named Entity Recognition (NER) in Python.mp4 | 70.2 MB |
| 10. Named Entity Recognition (NER) in Python.srt | 9.6 KB |
| 11. Text Summarization.mp4 | 24.1 MB |
| 11. Text Summarization.srt | 7.1 KB |
| 12. Text Summarization in Python.mp4 | 45.5 MB |
| 12. Text Summarization in Python.srt | 7.6 KB |
| 13. Neural Machine Translation.mp4 | 28.1 MB |
| 13. Neural Machine Translation.srt | 8.1 KB |
| 14. Neural Machine Translation in Python.mp4 | 64.1 MB |
| 14. Neural Machine Translation in Python.srt | 9.7 KB |
| 15. Question Answering.mp4 | 40.1 MB |
| 15. Question Answering.srt | 10.0 KB |
| 16. Question Answering in Python.mp4 | 48.2 MB |
| 16. Question Answering in Python.srt | 7.0 KB |
| 17. Zero-Shot Classification.mp4 | 30.1 MB |
| 17. Zero-Shot Classification.srt | 7.6 KB |
| 18. Zero-Shot Classification in Python.mp4 | 87.6 MB |
| 18. Zero-Shot Classification in Python.srt | 16.4 KB |
| 19. Beginner's Corner Section Summary.mp4 | 23.2 MB |
| 19. Beginner's Corner Section Summary.srt | 6.4 KB |
| 2. From RNNs to Attention and Transformers - Intuition.mp4 | 78.2 MB |
| 2. From RNNs to Attention and Transformers - Intuition.srt | 24.0 KB |
| 20. Suggestion Box.mp4 | 27.2 MB |
| 20. Suggestion Box.srt | 4.8 KB |
| 3. Sentiment Analysis.mp4 | 53.6 MB |
| 3. Sentiment Analysis.srt | 14.5 KB |
| 4. Sentiment Analysis in Python.mp4 | 97.1 MB |
| 4. Sentiment Analysis in Python.srt | 21.1 KB |
| 5. Text Generation.mp4 | 57.1 MB |
| 5. Text Generation.srt | 15.5 KB |
| 6. Text Generation in Python.mp4 | 86.3 MB |
| 6. Text Generation in Python.srt | 14.9 KB |
| 7. Masked Language Modeling (Article Spinner).mp4 | 67.3 MB |
| 7. Masked Language Modeling (Article Spinner).srt | 16.1 KB |
| 8. Masked Language Modeling (Article Spinner) in Python.mp4 | 67.1 MB |
| 8. Masked Language Modeling (Article Spinner) in Python.srt | 9.2 KB |
| 9. Named Entity Recognition (NER).mp4 | 22.0 MB |
| 9. Named Entity Recognition (NER).srt | 6.2 KB |
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. Fine-Tuning Section Introduction.mp4 | 20.2 MB |
| 1. Fine-Tuning Section Introduction.srt | 6.1 KB |
| 10. Fine-Tuning Transformers with Custom Dataset.mp4 | 106.9 MB |
| 10. Fine-Tuning Transformers with Custom Dataset.srt | 15.1 KB |
| 11. Hugging Face AutoConfig.mp4 | 40.9 MB |
| 11. Hugging Face AutoConfig.srt | 6.0 KB |
| 12. Fine-Tuning with Multiple Inputs (Textual Entailment).mp4 | 28.4 MB |
| 12. Fine-Tuning with Multiple Inputs (Textual Entailment).srt | 10.3 KB |
| 13. Fine-Tuning Transformers with Multiple Inputs in Python.mp4 | 56.7 MB |
| 13. Fine-Tuning Transformers with Multiple Inputs in Python.srt | 6.6 KB |
| 14. Fine-Tuning Section Summary.mp4 | 15.8 MB |
| 14. Fine-Tuning Section Summary.srt | 4.1 KB |
| 2. Text Preprocessing and Tokenization Review.mp4 | 63.2 MB |
| 2. Text Preprocessing and Tokenization Review.srt | 18.2 KB |
| 3. Models and Tokenizers.mp4 | 64.6 MB |
| 3. Models and Tokenizers.srt | 20.6 KB |
| 4. Models and Tokenizers in Python.mp4 | 84.3 MB |
| 4. Models and Tokenizers in Python.srt | 14.1 KB |
| 5. Transfer Learning & Fine-Tuning (pt 1).mp4 | 59.8 MB |
| 5. Transfer Learning & Fine-Tuning (pt 1).srt | 12.7 KB |
| 6. Transfer Learning & Fine-Tuning (pt 2).mp4 | 49.3 MB |
| 6. Transfer Learning & Fine-Tuning (pt 2).srt | 14.6 KB |
| 7. Transfer Learning & Fine-Tuning (pt 3).mp4 | 56.7 MB |
| 7. Transfer Learning & Fine-Tuning (pt 3).srt | 13.7 KB |
| 8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.mp4 | 58.4 MB |
| 8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.srt | 16.9 KB |
| 9. Fine-Tuning Sentiment Analysis in Python.mp4 | 130.8 MB |
| 9. Fine-Tuning Sentiment Analysis in Python.srt | 19.3 KB |
| 1. Token Classification Section Introduction.mp4 | 35.8 MB |
| 1. Token Classification Section Introduction.srt | 9.6 KB |
| 10. Metrics (Code).mp4 | 39.3 MB |
| 10. Metrics (Code).srt | 6.1 KB |
| 11. Model and Trainer (Code Preparation).mp4 | 10.8 MB |
| 11. Model and Trainer (Code Preparation).srt | 2.9 KB |
| 12. Model and Trainer (Code).mp4 | 22.2 MB |
| 12. Model and Trainer (Code).srt | 3.1 KB |
| 13. POS Tagging & Custom Datasets (Exercise Prompt).mp4 | 21.3 MB |
| 13. POS Tagging & Custom Datasets (Exercise Prompt).srt | 6.8 KB |
| 14. POS Tagging & Custom Datasets (Solution).mp4 | 115.1 MB |
| 14. POS Tagging & Custom Datasets (Solution).srt | 17.9 KB |
| 15. Token Classification Section Summary.mp4 | 8.0 MB |
| 15. Token Classification Section Summary.srt | 2.6 KB |
| 2. Data & Tokenizer (Code Preparation).mp4 | 19.3 MB |
| 2. Data & Tokenizer (Code Preparation).srt | 6.8 KB |
| 3. Data & Tokenizer (Code).mp4 | 42.7 MB |
| 3. Data & Tokenizer (Code).srt | 9.2 KB |
| 4. Target Alignment (Code Preparation).mp4 | 43.0 MB |
| 4. Target Alignment (Code Preparation).srt | 13.8 KB |
| 5. Create Tokenized Dataset (Code Preparation).mp4 | 18.3 MB |
| 5. Create Tokenized Dataset (Code Preparation).srt | 5.0 KB |
| 6. Target Alignment (Code).mp4 | 61.7 MB |
| 6. Target Alignment (Code).srt | 11.9 KB |
| 7. Data Collator (Code Preparation).mp4 | 22.1 MB |
| 7. Data Collator (Code Preparation).srt | 4.9 KB |
| 8. Data Collator (Code).mp4 | 16.9 MB |
| 8. Data Collator (Code).srt | 3.7 KB |
| 9. Metrics (Code Preparation).mp4 | 33.4 MB |
| 9. Metrics (Code Preparation).srt | 9.1 KB |
| 1. Translation Section Introduction.mp4 | 18.2 MB |
| 1. Translation Section Introduction.srt | 6.4 KB |
| 10. Train & Evaluate (Code Preparation).mp4 | 21.3 MB |
| 10. Train & Evaluate (Code Preparation).srt | 5.6 KB |
| 11. Train & Evaluate (Code).mp4 | 35.7 MB |
| 11. Train & Evaluate (Code).srt | 4.6 KB |
| 12. Translation Section Summary.mp4 | 9.8 MB |
| 12. Translation Section Summary.srt | 3.3 KB |
| 2. Data & Tokenizer (Code Preparation).mp4 | 24.5 MB |
| 2. Data & Tokenizer (Code Preparation).srt | 7.5 KB |
| 3. Things Move Fast.mp4 | 6.1 MB |
| 3. Things Move Fast.srt | 2.4 KB |
| 4. Data & Tokenizer (Code).mp4 | 34.1 MB |
| 4. Data & Tokenizer (Code).srt | 6.4 KB |
| 5. Aside Seq2Seq Basics (Optional).mp4 | 37.1 MB |
| 5. Aside Seq2Seq Basics (Optional).srt | 15.2 KB |
| 6. Model Inputs (Code Preparation).mp4 | 32.4 MB |
| 6. Model Inputs (Code Preparation).srt | 11.2 KB |
| 7. Model Inputs (Code).mp4 | 51.4 MB |
| 7. Model Inputs (Code).srt | 7.8 KB |
| 8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).mp4 | 19.3 MB |
| 8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).srt | 5.0 KB |
| 9. Translation Metrics (BLEU Score & BERT Score) (Code).mp4 | 43.3 MB |
| 9. Translation Metrics (BLEU Score & BERT Score) (Code).srt | 6.3 KB |
| 1. Question-Answering Section Introduction.mp4 | 21.5 MB |
| 1. Question-Answering Section Introduction.srt | 6.1 KB |
| 10. Question-Answering Metrics.mp4 | 16.5 MB |
| 10. Question-Answering Metrics.srt | 4.7 KB |
| 11. Question-Answering Metrics in Python.mp4 | 22.9 MB |
| 11. Question-Answering Metrics in Python.srt | 3.0 KB |
| 12. From Logits to Answers.mp4 | 95.6 MB |
| 12. From Logits to Answers.srt | 27.7 KB |
| 13. From Logits to Answers in Python.mp4 | 120.6 MB |
| 13. From Logits to Answers in Python.srt | 16.9 KB |
| 14. Computing Metrics.mp4 | 24.9 MB |
| 14. Computing Metrics.srt | 6.6 KB |
| 15. Computing Metrics in Python.mp4 | 44.3 MB |
| 15. Computing Metrics in Python.srt | 6.1 KB |
| 16. Train and Evaluate.mp4 | 14.1 MB |
| 16. Train and Evaluate.srt | 3.3 KB |
| 17. Train and Evaluate in Python.mp4 | 37.8 MB |
| 17. Train and Evaluate in Python.srt | 4.7 KB |
| 18. Question-Answering Section Summary.mp4 | 14.2 MB |
| 18. Question-Answering Section Summary.srt | 5.0 KB |
| 2. Exploring the Dataset (SQuAD).mp4 | 20.2 MB |
| 2. Exploring the Dataset (SQuAD).srt | 5.7 KB |
| 3. Exploring the Dataset (SQuAD) in Python.mp4 | 39.9 MB |
| 3. Exploring the Dataset (SQuAD) in Python.srt | 4.7 KB |
| 4. Using the Tokenizer.mp4 | 34.5 MB |
| 4. Using the Tokenizer.srt | 10.8 KB |
| 5. Using the Tokenizer in Python.mp4 | 72.1 MB |
| 5. Using the Tokenizer in Python.srt | 13.1 KB |
| 6. Aligning the Targets.mp4 | 69.1 MB |
| 6. Aligning the Targets.srt | 19.3 KB |
| 7. Aligning the Targets in Python.mp4 | 103.3 MB |
| 7. Aligning the Targets in Python.srt | 18.8 KB |
| 8. Applying the Tokenizer.mp4 | 45.0 MB |
| 8. Applying the Tokenizer.srt | 12.3 KB |
| 9. Applying the Tokenizer in Python.mp4 | 76.5 MB |
| 9. Applying the Tokenizer in Python.srt | 12.0 KB |
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. Theory Section Introduction.mp4 | 17.1 MB |
| 1. Theory Section Introduction.srt | 6.9 KB |
| 10. Decoder Architecture.mp4 | 49.6 MB |
| 10. Decoder Architecture.srt | 14.6 KB |
| 11. Encoder-Decoder Architecture.mp4 | 39.7 MB |
| 11. Encoder-Decoder Architecture.srt | 11.4 KB |
| 12. BERT.mp4 | 23.3 MB |
| 12. BERT.srt | 6.1 KB |
| 13. GPT.mp4 | 31.2 MB |
| 13. GPT.srt | 8.6 KB |
| 14. GPT-2.mp4 | 29.7 MB |
| 14. GPT-2.srt | 8.3 KB |
| 15. GPT-3.mp4 | 24.0 MB |
| 15. GPT-3.srt | 6.6 KB |
| 16. Theory Section Summary.mp4 | 21.0 MB |
| 16. Theory Section Summary.srt | 6.3 KB |
| 2. Basic Self-Attention.mp4 | 37.0 MB |
| 2. Basic Self-Attention.srt | 12.4 KB |
| 3. Self-Attention & Scaled Dot-Product Attention.mp4 | 64.3 MB |
| 3. Self-Attention & Scaled Dot-Product Attention.srt | 23.9 KB |
| 4. Attention Efficiency.mp4 | 21.6 MB |
| 4. Attention Efficiency.srt | 5.9 KB |
| 5. Attention Mask.mp4 | 15.1 MB |
| 5. Attention Mask.srt | 5.0 KB |
| 6. Multi-Head Attention.mp4 | 33.7 MB |
| 6. Multi-Head Attention.srt | 9.4 KB |
| 7. Transformer Block.mp4 | 29.5 MB |
| 7. Transformer Block.srt | 9.5 KB |
| 8. Positional Encodings.mp4 | 29.0 MB |
| 8. Positional Encodings.srt | 9.5 KB |
| 9. Encoder Architecture.mp4 | 25.2 MB |
| 9. Encoder Architecture.srt | 8.6 KB |
| 1. Implementation Section Introduction.mp4 | 25.6 MB |
| 1. Implementation Section Introduction.srt | 8.5 KB |
| 10. How to Train a Causal Language Model From Scratch.mp4 | 120.4 MB |
| 10. How to Train a Causal Language Model From Scratch.srt | 20.1 KB |
| 11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).mp4 | 94.0 MB |
| 11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).srt | 13.4 KB |
| 12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).mp4 | 95.2 MB |
| 12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).srt | 15.0 KB |
| 13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).mp4 | 108.6 MB |
| 13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).srt | 17.5 KB |
| 14. Implementation Section Summary.mp4 | 10.6 MB |
| 14. Implementation Section Summary.srt | 2.0 KB |
| 2. Encoder Implementation Plan & Outline.mp4 | 23.0 MB |
| 2. Encoder Implementation Plan & Outline.srt | 8.4 KB |
| 3. How to Implement Multihead Attention From Scratch.mp4 | 93.4 MB |
| 3. How to Implement Multihead Attention From Scratch.srt | 15.5 KB |
| 4. How to Implement the Transformer Block From Scratch.mp4 | 14.9 MB |
| 4. How to Implement the Transformer Block From Scratch.srt | 2.4 KB |
| 5. How to Implement Positional Encoding From Scratch.mp4 | 35.9 MB |
| 5. How to Implement Positional Encoding From Scratch.srt | 6.3 KB |
| 6. How to Implement Transformer Encoder From Scratch.mp4 | 27.0 MB |
| 6. How to Implement Transformer Encoder From Scratch.srt | 4.8 KB |
| 7. Train and Evaluate Encoder From Scratch.mp4 | 89.3 MB |
| 7. Train and Evaluate Encoder From Scratch.srt | 12.3 KB |
| 8. How to Implement Causal Self-Attention From Scratch.mp4 | 39.2 MB |
| 8. How to Implement Causal Self-Attention From Scratch.srt | 5.7 KB |
| 9. How to Implement a Transformer Decoder (GPT) From Scratch.mp4 | 27.3 MB |
| 9. How to Implement a Transformer Decoder (GPT) From Scratch.srt | 4.9 KB |
Name
DL
Uploader
Size
S/L
Added
-
917.6 MB
[7
/
2]
2025-03-07
| Uploaded by freecoursewb | Size 917.6 MB | Health [ 7 /2 ] | Added 2025-03-07 |
-
737.2 MB
[39
/
3]
2024-12-02
| Uploaded by FreeCourseWeb | Size 737.2 MB | Health [ 39 /3 ] | Added 2024-12-02 |
-
434.2 MB
[10
/
3]
2024-10-24
| Uploaded by FreeCourseWeb | Size 434.2 MB | Health [ 10 /3 ] | Added 2024-10-24 |
-
336.1 MB
[6
/
0]
2024-09-11
| Uploaded by FreeCourseWeb | Size 336.1 MB | Health [ 6 /0 ] | Added 2024-09-11 |
NOTE
SOURCE: Udemy Data Science Transformers for Natural Language Processing
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COVER
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