Udemy - Data Science: Transformers for Natural Language Processin...

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Udemy - Data Science: Transformers for Natural Language Processing

ChatGPT, GPT-4, BERT, Deep Learning, Machine Learning, & NLP with Hugging Face, Attention in Python, Tensorflow, PyTorch.

Created by Lazy Programmer Team,  Lazy Programmer Inc.
Last updated 8/2023
English
English [Auto]

Files:

[FreeCourseSite.com] Udemy - Data Science Transformers for Natural Language Processing 0. Websites you may like
  • [CourseClub.Me].url (0.1 KB)
  • [FreeCourseSite.com].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)
1. Welcome
  • 1. Introduction.mp4 (34.6 MB)
  • 1. Introduction.srt (5.6 KB)
  • 2. Outline.mp4 (50.7 MB)
  • 2. Outline.srt (13.5 KB)
10. Extras
  • 1. Data Links.html (0.3 KB)
11. Setting Up Your Environment FAQ
  • 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)
12. Extra Help With Python Coding for Beginners FAQ
  • 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)
13. Effective Learning Strategies for Machine Learning FAQ 0. Websites you may like
  • [CourseClub.Me].url (0.1 KB)
  • [FreeCourseSite.com].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)
  • 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)
    • 14. Appendix FAQ Finale
    • 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)
    2. Getting Setup
    • 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 (0.2 KB)
    • 1.2 Github Link.html (0.1 KB)
    • 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 (0.1 KB)
    • 3.2 Data Links.html (0.2 KB)
    • 3.3 Github Link.html (0.1 KB)
    • 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)
    3. Beginner's Corner
    • 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)
    4. Fine-Tuning (Intermediate) 0. Websites you may like
    • [CourseClub.Me].url (0.1 KB)
    • [FreeCourseSite.com].url (0.1 KB)
    • [GigaCourse.Com].url (0.0 KB)
    • 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)
      • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)
      • 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)
      6. Seq2Seq and Neural Machine Translation (Intermediate)
      • 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)
      7. Question-Answering (Advanced)
      • 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)
      8. Transformers and Attention Theory (Advanced) 0. Websites you may like
      • [CourseClub.Me].url (0.1 KB)
      • [FreeCourseSite.com].url (0.1 KB)
      • [GigaCourse.Com].url (0.0 KB)
      • 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)
        • 9. Implement Transformers From Scratch (Advanced)
        • 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)

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