GetFreeCourses.Co-Udemy-Data Science Transformers for Natural Language Processing

Creation Time	April 21, 2024, 9:43 p.m.
Last Access Time	Nov. 24, 2024, 5:27 a.m.
File Size	5.6 GB
Keywords	Natural Language for Science Processing Co-Udemy-Data GetFreeCourses Transformers
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4. Fine-Tuning (Intermediate)/9. Fine-Tuning Sentiment Analysis in Python.mp4 130.8 MB
7. Question-Answering (Advanced)/13. From Logits to Answers in Python.mp4 120.6 MB
9. Implement Transformers From Scratch (Advanced)/10. How to Train a Causal Language Model From Scratch.mp4 120.4 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/14. POS Tagging & Custom Datasets (Solution).mp4 115.1 MB
9. Implement Transformers From Scratch (Advanced)/13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).mp4 108.6 MB
13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108.2 MB
4. Fine-Tuning (Intermediate)/10. Fine-Tuning Transformers with Custom Dataset.mp4 106.9 MB
7. Question-Answering (Advanced)/7. Aligning the Targets in Python.mp4 103.3 MB
3. Beginner's Corner/4. Sentiment Analysis in Python.mp4 97.1 MB
7. Question-Answering (Advanced)/12. From Logits to Answers.mp4 95.6 MB
9. Implement Transformers From Scratch (Advanced)/12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).mp4 95.2 MB
9. Implement Transformers From Scratch (Advanced)/11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).mp4 94.0 MB
9. Implement Transformers From Scratch (Advanced)/3. How to Implement Multihead Attention From Scratch.mp4 93.4 MB
9. Implement Transformers From Scratch (Advanced)/7. Train and Evaluate Encoder From Scratch.mp4 89.3 MB
3. Beginner's Corner/18. Zero-Shot Classification in Python.mp4 87.6 MB
3. Beginner's Corner/6. Text Generation in Python.mp4 86.3 MB
4. Fine-Tuning (Intermediate)/4. Models and Tokenizers in Python.mp4 84.3 MB
13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.7 MB
3. Beginner's Corner/2. From RNNs to Attention and Transformers - Intuition.mp4 78.2 MB
7. Question-Answering (Advanced)/9. Applying the Tokenizer in Python.mp4 76.5 MB
7. Question-Answering (Advanced)/5. Using the Tokenizer in Python.mp4 72.1 MB
12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 71.8 MB
3. Beginner's Corner/10. Named Entity Recognition (NER) in Python.mp4 70.2 MB
12. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4 69.4 MB
7. Question-Answering (Advanced)/6. Aligning the Targets.mp4 69.1 MB
3. Beginner's Corner/7. Masked Language Modeling (Article Spinner).mp4 67.3 MB
3. Beginner's Corner/8. Masked Language Modeling (Article Spinner) in Python.mp4 67.1 MB
4. Fine-Tuning (Intermediate)/3. Models and Tokenizers.mp4 64.6 MB
8. Transformers and Attention Theory (Advanced)/3. Self-Attention & Scaled Dot-Product Attention.mp4 64.3 MB
3. Beginner's Corner/14. Neural Machine Translation in Python.mp4 64.1 MB
2. Getting Setup/2. How to use Github & Extra Coding Tips (Optional).mp4 63.9 MB
4. Fine-Tuning (Intermediate)/2. Text Preprocessing and Tokenization Review.mp4 63.2 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/6. Target Alignment (Code).mp4 61.7 MB
4. Fine-Tuning (Intermediate)/5. Transfer Learning & Fine-Tuning (pt 1).mp4 59.8 MB
4. Fine-Tuning (Intermediate)/8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.mp4 58.4 MB
3. Beginner's Corner/5. Text Generation.mp4 57.1 MB
4. Fine-Tuning (Intermediate)/7. Transfer Learning & Fine-Tuning (pt 3).mp4 56.7 MB
4. Fine-Tuning (Intermediate)/13. Fine-Tuning Transformers with Multiple Inputs in Python.mp4 56.7 MB
3. Beginner's Corner/3. Sentiment Analysis.mp4 53.6 MB
11. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.mp4 52.6 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/7. Model Inputs (Code).mp4 51.4 MB
1. Welcome/2. Outline.mp4 50.7 MB
3. Beginner's Corner/1. Beginner's Corner Section Introduction.mp4 49.7 MB
8. Transformers and Attention Theory (Advanced)/10. Decoder Architecture.mp4 49.6 MB
4. Fine-Tuning (Intermediate)/6. Transfer Learning & Fine-Tuning (pt 2).mp4 49.3 MB
12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 49.1 MB
3. Beginner's Corner/16. Question Answering in Python.mp4 48.2 MB
3. Beginner's Corner/12. Text Summarization in Python.mp4 45.5 MB
7. Question-Answering (Advanced)/8. Applying the Tokenizer.mp4 45.0 MB
7. Question-Answering (Advanced)/15. Computing Metrics in Python.mp4 44.3 MB
11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.6 MB
2. Getting Setup/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 43.6 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/9. Translation Metrics (BLEU Score & BERT Score) (Code).mp4 43.3 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/4. Target Alignment (Code Preparation).mp4 43.0 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/3. Data & Tokenizer (Code).mp4 42.7 MB
2. Getting Setup/5. How to Succeed in This Course.mp4 41.2 MB
4. Fine-Tuning (Intermediate)/11. Hugging Face AutoConfig.mp4 40.9 MB
3. Beginner's Corner/15. Question Answering.mp4 40.1 MB
14. Appendix FAQ Finale/2. BONUS.mp4 39.9 MB
7. Question-Answering (Advanced)/3. Exploring the Dataset (SQuAD) in Python.mp4 39.9 MB
8. Transformers and Attention Theory (Advanced)/11. Encoder-Decoder Architecture.mp4 39.7 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/10. Metrics (Code).mp4 39.3 MB
9. Implement Transformers From Scratch (Advanced)/8. How to Implement Causal Self-Attention From Scratch.mp4 39.2 MB
13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
7. Question-Answering (Advanced)/17. Train and Evaluate in Python.mp4 37.8 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/5. Aside Seq2Seq Basics (Optional).mp4 37.1 MB
8. Transformers and Attention Theory (Advanced)/2. Basic Self-Attention.mp4 37.0 MB
9. Implement Transformers From Scratch (Advanced)/5. How to Implement Positional Encoding From Scratch.mp4 35.9 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/1. Token Classification Section Introduction.mp4 35.8 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/11. Train & Evaluate (Code).mp4 35.7 MB
1. Welcome/1. Introduction.mp4 34.6 MB
7. Question-Answering (Advanced)/4. Using the Tokenizer.mp4 34.5 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/4. Data & Tokenizer (Code).mp4 34.1 MB
8. Transformers and Attention Theory (Advanced)/6. Multi-Head Attention.mp4 33.7 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/9. Metrics (Code Preparation).mp4 33.4 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/6. Model Inputs (Code Preparation).mp4 32.4 MB
8. Transformers and Attention Theory (Advanced)/13. GPT.mp4 31.2 MB
3. Beginner's Corner/17. Zero-Shot Classification.mp4 30.1 MB
8. Transformers and Attention Theory (Advanced)/14. GPT-2.mp4 29.7 MB
8. Transformers and Attention Theory (Advanced)/7. Transformer Block.mp4 29.5 MB
8. Transformers and Attention Theory (Advanced)/8. Positional Encodings.mp4 29.0 MB
4. Fine-Tuning (Intermediate)/12. Fine-Tuning with Multiple Inputs (Textual Entailment).mp4 28.4 MB
3. Beginner's Corner/13. Neural Machine Translation.mp4 28.1 MB
9. Implement Transformers From Scratch (Advanced)/9. How to Implement a Transformer Decoder (GPT) From Scratch.mp4 27.3 MB
3. Beginner's Corner/20. Suggestion Box.mp4 27.2 MB
9. Implement Transformers From Scratch (Advanced)/6. How to Implement Transformer Encoder From Scratch.mp4 27.0 MB
2. Getting Setup/4. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 26.7 MB
9. Implement Transformers From Scratch (Advanced)/1. Implementation Section Introduction.mp4 25.6 MB
8. Transformers and Attention Theory (Advanced)/9. Encoder Architecture.mp4 25.2 MB
7. Question-Answering (Advanced)/14. Computing Metrics.mp4 24.9 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/2. Data & Tokenizer (Code Preparation).mp4 24.5 MB
3. Beginner's Corner/11. Text Summarization.mp4 24.1 MB
8. Transformers and Attention Theory (Advanced)/15. GPT-3.mp4 24.0 MB
8. Transformers and Attention Theory (Advanced)/12. BERT.mp4 23.3 MB
3. Beginner's Corner/19. Beginner's Corner Section Summary.mp4 23.2 MB
9. Implement Transformers From Scratch (Advanced)/2. Encoder Implementation Plan & Outline.mp4 23.0 MB
7. Question-Answering (Advanced)/11. Question-Answering Metrics in Python.mp4 22.9 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/12. Model and Trainer (Code).mp4 22.2 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/7. Data Collator (Code Preparation).mp4 22.1 MB
3. Beginner's Corner/9. Named Entity Recognition (NER).mp4 22.0 MB
8. Transformers and Attention Theory (Advanced)/4. Attention Efficiency.mp4 21.6 MB
7. Question-Answering (Advanced)/1. Question-Answering Section Introduction.mp4 21.5 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/13. POS Tagging & Custom Datasets (Exercise Prompt).mp4 21.3 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/10. Train & Evaluate (Code Preparation).mp4 21.3 MB
8. Transformers and Attention Theory (Advanced)/16. Theory Section Summary.mp4 21.0 MB
4. Fine-Tuning (Intermediate)/1. Fine-Tuning Section Introduction.mp4 20.2 MB
7. Question-Answering (Advanced)/2. Exploring the Dataset (SQuAD).mp4 20.2 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/2. Data & Tokenizer (Code Preparation).mp4 19.3 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).mp4 19.3 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/5. Create Tokenized Dataset (Code Preparation).mp4 18.3 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/1. Translation Section Introduction.mp4 18.2 MB
13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 17.9 MB
2. Getting Setup/3. Where to get the code, notebooks, and data.mp4 17.8 MB
8. Transformers and Attention Theory (Advanced)/1. Theory Section Introduction.mp4 17.1 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/8. Data Collator (Code).mp4 16.9 MB
7. Question-Answering (Advanced)/10. Question-Answering Metrics.mp4 16.5 MB
14. Appendix FAQ Finale/1. What is the Appendix.mp4 16.4 MB
4. Fine-Tuning (Intermediate)/14. Fine-Tuning Section Summary.mp4 15.8 MB
8. Transformers and Attention Theory (Advanced)/5. Attention Mask.mp4 15.1 MB
9. Implement Transformers From Scratch (Advanced)/4. How to Implement the Transformer Block From Scratch.mp4 14.9 MB
7. Question-Answering (Advanced)/18. Question-Answering Section Summary.mp4 14.2 MB
7. Question-Answering (Advanced)/16. Train and Evaluate.mp4 14.1 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/11. Model and Trainer (Code Preparation).mp4 10.8 MB
9. Implement Transformers From Scratch (Advanced)/14. Implementation Section Summary.mp4 10.6 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/12. Translation Section Summary.mp4 9.8 MB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/15. Token Classification Section Summary.mp4 8.0 MB
6. Seq2Seq and Neural Machine Translation (Intermediate)/3. Things Move Fast.mp4 6.1 MB
13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.7 KB
7. Question-Answering (Advanced)/12. From Logits to Answers.srt 27.7 KB
3. Beginner's Corner/2. From RNNs to Attention and Transformers - Intuition.srt 24.0 KB
8. Transformers and Attention Theory (Advanced)/3. Self-Attention & Scaled Dot-Product Attention.srt 23.9 KB
13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.9 KB
12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23.1 KB
3. Beginner's Corner/4. Sentiment Analysis in Python.srt 21.1 KB
4. Fine-Tuning (Intermediate)/3. Models and Tokenizers.srt 20.6 KB
11. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.srt 20.1 KB
9. Implement Transformers From Scratch (Advanced)/10. How to Train a Causal Language Model From Scratch.srt 20.1 KB
7. Question-Answering (Advanced)/6. Aligning the Targets.srt 19.3 KB
4. Fine-Tuning (Intermediate)/9. Fine-Tuning Sentiment Analysis in Python.srt 19.3 KB
7. Question-Answering (Advanced)/7. Aligning the Targets in Python.srt 18.8 KB
4. Fine-Tuning (Intermediate)/2. Text Preprocessing and Tokenization Review.srt 18.2 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/14. POS Tagging & Custom Datasets (Solution).srt 17.9 KB
9. Implement Transformers From Scratch (Advanced)/13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).srt 17.5 KB
13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17.1 KB
7. Question-Answering (Advanced)/13. From Logits to Answers in Python.srt 16.9 KB
4. Fine-Tuning (Intermediate)/8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.srt 16.9 KB
3. Beginner's Corner/18. Zero-Shot Classification in Python.srt 16.4 KB
3. Beginner's Corner/7. Masked Language Modeling (Article Spinner).srt 16.1 KB
11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15.8 KB
2. Getting Setup/2. How to use Github & Extra Coding Tips (Optional).srt 15.7 KB
9. Implement Transformers From Scratch (Advanced)/3. How to Implement Multihead Attention From Scratch.srt 15.5 KB
3. Beginner's Corner/5. Text Generation.srt 15.5 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/5. Aside Seq2Seq Basics (Optional).srt 15.2 KB
4. Fine-Tuning (Intermediate)/10. Fine-Tuning Transformers with Custom Dataset.srt 15.1 KB
3. Beginner's Corner/1. Beginner's Corner Section Introduction.srt 15.1 KB
9. Implement Transformers From Scratch (Advanced)/12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).srt 15.0 KB
12. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 14.9 KB
3. Beginner's Corner/6. Text Generation in Python.srt 14.9 KB
8. Transformers and Attention Theory (Advanced)/10. Decoder Architecture.srt 14.6 KB
4. Fine-Tuning (Intermediate)/6. Transfer Learning & Fine-Tuning (pt 2).srt 14.6 KB
3. Beginner's Corner/3. Sentiment Analysis.srt 14.5 KB
13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 14.5 KB
4. Fine-Tuning (Intermediate)/4. Models and Tokenizers in Python.srt 14.1 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/4. Target Alignment (Code Preparation).srt 13.8 KB
4. Fine-Tuning (Intermediate)/7. Transfer Learning & Fine-Tuning (pt 3).srt 13.7 KB
1. Welcome/2. Outline.srt 13.5 KB
9. Implement Transformers From Scratch (Advanced)/11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).srt 13.4 KB
12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13.2 KB
7. Question-Answering (Advanced)/5. Using the Tokenizer in Python.srt 13.1 KB
2. Getting Setup/5. How to Succeed in This Course.srt 13.0 KB
4. Fine-Tuning (Intermediate)/5. Transfer Learning & Fine-Tuning (pt 1).srt 12.7 KB
8. Transformers and Attention Theory (Advanced)/2. Basic Self-Attention.srt 12.4 KB
9. Implement Transformers From Scratch (Advanced)/7. Train and Evaluate Encoder From Scratch.srt 12.3 KB
7. Question-Answering (Advanced)/8. Applying the Tokenizer.srt 12.3 KB
7. Question-Answering (Advanced)/9. Applying the Tokenizer in Python.srt 12.0 KB
2. Getting Setup/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt 12.0 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/6. Target Alignment (Code).srt 11.9 KB
8. Transformers and Attention Theory (Advanced)/11. Encoder-Decoder Architecture.srt 11.4 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/6. Model Inputs (Code Preparation).srt 11.2 KB
7. Question-Answering (Advanced)/4. Using the Tokenizer.srt 10.8 KB
4. Fine-Tuning (Intermediate)/12. Fine-Tuning with Multiple Inputs (Textual Entailment).srt 10.3 KB
3. Beginner's Corner/15. Question Answering.srt 10.0 KB
3. Beginner's Corner/14. Neural Machine Translation in Python.srt 9.7 KB
3. Beginner's Corner/10. Named Entity Recognition (NER) in Python.srt 9.6 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/1. Token Classification Section Introduction.srt 9.6 KB
8. Transformers and Attention Theory (Advanced)/7. Transformer Block.srt 9.5 KB
8. Transformers and Attention Theory (Advanced)/8. Positional Encodings.srt 9.5 KB
8. Transformers and Attention Theory (Advanced)/6. Multi-Head Attention.srt 9.4 KB
3. Beginner's Corner/8. Masked Language Modeling (Article Spinner) in Python.srt 9.2 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/3. Data & Tokenizer (Code).srt 9.2 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/9. Metrics (Code Preparation).srt 9.1 KB
8. Transformers and Attention Theory (Advanced)/13. GPT.srt 8.6 KB
8. Transformers and Attention Theory (Advanced)/9. Encoder Architecture.srt 8.6 KB
9. Implement Transformers From Scratch (Advanced)/1. Implementation Section Introduction.srt 8.5 KB
9. Implement Transformers From Scratch (Advanced)/2. Encoder Implementation Plan & Outline.srt 8.4 KB
8. Transformers and Attention Theory (Advanced)/14. GPT-2.srt 8.3 KB
3. Beginner's Corner/13. Neural Machine Translation.srt 8.1 KB
14. Appendix FAQ Finale/2. BONUS.srt 7.9 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/7. Model Inputs (Code).srt 7.8 KB
3. Beginner's Corner/17. Zero-Shot Classification.srt 7.6 KB
3. Beginner's Corner/12. Text Summarization in Python.srt 7.6 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/2. Data & Tokenizer (Code Preparation).srt 7.5 KB
2. Getting Setup/4. Are You Beginner, Intermediate, or Advanced All are OK!.srt 7.1 KB
3. Beginner's Corner/11. Text Summarization.srt 7.1 KB
3. Beginner's Corner/16. Question Answering in Python.srt 7.0 KB
8. Transformers and Attention Theory (Advanced)/1. Theory Section Introduction.srt 6.9 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/13. POS Tagging & Custom Datasets (Exercise Prompt).srt 6.8 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/2. Data & Tokenizer (Code Preparation).srt 6.8 KB
7. Question-Answering (Advanced)/14. Computing Metrics.srt 6.6 KB
4. Fine-Tuning (Intermediate)/13. Fine-Tuning Transformers with Multiple Inputs in Python.srt 6.6 KB
8. Transformers and Attention Theory (Advanced)/15. GPT-3.srt 6.6 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/4. Data & Tokenizer (Code).srt 6.4 KB
3. Beginner's Corner/19. Beginner's Corner Section Summary.srt 6.4 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/1. Translation Section Introduction.srt 6.4 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/9. Translation Metrics (BLEU Score & BERT Score) (Code).srt 6.3 KB
8. Transformers and Attention Theory (Advanced)/16. Theory Section Summary.srt 6.3 KB
9. Implement Transformers From Scratch (Advanced)/5. How to Implement Positional Encoding From Scratch.srt 6.3 KB
3. Beginner's Corner/9. Named Entity Recognition (NER).srt 6.2 KB
4. Fine-Tuning (Intermediate)/1. Fine-Tuning Section Introduction.srt 6.1 KB
8. Transformers and Attention Theory (Advanced)/12. BERT.srt 6.1 KB
7. Question-Answering (Advanced)/1. Question-Answering Section Introduction.srt 6.1 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/10. Metrics (Code).srt 6.1 KB
7. Question-Answering (Advanced)/15. Computing Metrics in Python.srt 6.1 KB
4. Fine-Tuning (Intermediate)/11. Hugging Face AutoConfig.srt 6.0 KB
8. Transformers and Attention Theory (Advanced)/4. Attention Efficiency.srt 5.9 KB
7. Question-Answering (Advanced)/2. Exploring the Dataset (SQuAD).srt 5.7 KB
9. Implement Transformers From Scratch (Advanced)/8. How to Implement Causal Self-Attention From Scratch.srt 5.7 KB
1. Welcome/1. Introduction.srt 5.6 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/10. Train & Evaluate (Code Preparation).srt 5.6 KB
7. Question-Answering (Advanced)/18. Question-Answering Section Summary.srt 5.0 KB
8. Transformers and Attention Theory (Advanced)/5. Attention Mask.srt 5.0 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/5. Create Tokenized Dataset (Code Preparation).srt 5.0 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).srt 5.0 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/7. Data Collator (Code Preparation).srt 4.9 KB
9. Implement Transformers From Scratch (Advanced)/9. How to Implement a Transformer Decoder (GPT) From Scratch.srt 4.9 KB
3. Beginner's Corner/20. Suggestion Box.srt 4.8 KB
9. Implement Transformers From Scratch (Advanced)/6. How to Implement Transformer Encoder From Scratch.srt 4.8 KB
7. Question-Answering (Advanced)/10. Question-Answering Metrics.srt 4.7 KB
7. Question-Answering (Advanced)/17. Train and Evaluate in Python.srt 4.7 KB
7. Question-Answering (Advanced)/3. Exploring the Dataset (SQuAD) in Python.srt 4.7 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/11. Train & Evaluate (Code).srt 4.6 KB
2. Getting Setup/3. Where to get the code, notebooks, and data.srt 4.3 KB
4. Fine-Tuning (Intermediate)/14. Fine-Tuning Section Summary.srt 4.1 KB
14. Appendix FAQ Finale/1. What is the Appendix.srt 3.9 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/8. Data Collator (Code).srt 3.7 KB
7. Question-Answering (Advanced)/16. Train and Evaluate.srt 3.3 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/12. Translation Section Summary.srt 3.3 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/12. Model and Trainer (Code).srt 3.1 KB
7. Question-Answering (Advanced)/11. Question-Answering Metrics in Python.srt 3.0 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/11. Model and Trainer (Code Preparation).srt 2.9 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/15. Token Classification Section Summary.srt 2.6 KB
9. Implement Transformers From Scratch (Advanced)/4. How to Implement the Transformer Block From Scratch.srt 2.4 KB
6. Seq2Seq and Neural Machine Translation (Intermediate)/3. Things Move Fast.srt 2.4 KB
9. Implement Transformers From Scratch (Advanced)/14. Implementation Section Summary.srt 2.0 KB
10. Extras/1. Data Links.html 256 bytes
How you can help GetFreeCourses.Co.txt 182 bytes
2. Getting Setup/1.1 Data Links.html 157 bytes
2. Getting Setup/3.2 Data Links.html 157 bytes
2. Getting Setup/1.2 Github Link.html 145 bytes
2. Getting Setup/3.3 Github Link.html 145 bytes
2. Getting Setup/3.1 Code Link.html 125 bytes
11. Setting Up Your Environment FAQ/GetFreeCourses.Co.url 116 bytes
13. Effective Learning Strategies for Machine Learning FAQ/GetFreeCourses.Co.url 116 bytes
4. Fine-Tuning (Intermediate)/GetFreeCourses.Co.url 116 bytes
7. Question-Answering (Advanced)/GetFreeCourses.Co.url 116 bytes
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