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GetFreeCourses.Co-Udemy-Data Science Transformers for Natural Language Processing
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5.65 GB
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GetFreeCourses.Co-Udemy-Data Science Transformers for Natural Language Processing
4. Fine-Tuning (Intermediate)
9. Fine-Tuning Sentiment Analysis in Python.mp4
- 130.77 MB
10. Fine-Tuning Transformers with Custom Dataset.mp4
- 106.85 MB
4. Models and Tokenizers in Python.mp4
- 84.26 MB
3. Models and Tokenizers.mp4
- 64.57 MB
2. Text Preprocessing and Tokenization Review.mp4
- 63.16 MB
5. Transfer Learning & Fine-Tuning (pt 1).mp4
- 59.83 MB
8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.mp4
- 58.43 MB
7. Transfer Learning & Fine-Tuning (pt 3).mp4
- 56.66 MB
13. Fine-Tuning Transformers with Multiple Inputs in Python.mp4
- 56.66 MB
6. Transfer Learning & Fine-Tuning (pt 2).mp4
- 49.31 MB
11. Hugging Face AutoConfig.mp4
- 40.86 MB
12. Fine-Tuning with Multiple Inputs (Textual Entailment).mp4
- 28.42 MB
1. Fine-Tuning Section Introduction.mp4
- 20.16 MB
14. Fine-Tuning Section Summary.mp4
- 15.78 MB
3. Models and Tokenizers.srt
- 20.6 KB
9. Fine-Tuning Sentiment Analysis in Python.srt
- 19.29 KB
2. Text Preprocessing and Tokenization Review.srt
- 18.22 KB
8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.srt
- 16.85 KB
10. Fine-Tuning Transformers with Custom Dataset.srt
- 15.1 KB
6. Transfer Learning & Fine-Tuning (pt 2).srt
- 14.58 KB
4. Models and Tokenizers in Python.srt
- 14.12 KB
7. Transfer Learning & Fine-Tuning (pt 3).srt
- 13.67 KB
5. Transfer Learning & Fine-Tuning (pt 1).srt
- 12.69 KB
12. Fine-Tuning with Multiple Inputs (Textual Entailment).srt
- 10.32 KB
13. Fine-Tuning Transformers with Multiple Inputs in Python.srt
- 6.62 KB
1. Fine-Tuning Section Introduction.srt
- 6.14 KB
11. Hugging Face AutoConfig.srt
- 6.03 KB
14. Fine-Tuning Section Summary.srt
- 4.11 KB
GetFreeCourses.Co.url
- 116 B
7. Question-Answering (Advanced)
13. From Logits to Answers in Python.mp4
- 120.62 MB
7. Aligning the Targets in Python.mp4
- 103.33 MB
12. From Logits to Answers.mp4
- 95.56 MB
9. Applying the Tokenizer in Python.mp4
- 76.5 MB
5. Using the Tokenizer in Python.mp4
- 72.13 MB
6. Aligning the Targets.mp4
- 69.08 MB
8. Applying the Tokenizer.mp4
- 45.05 MB
15. Computing Metrics in Python.mp4
- 44.26 MB
3. Exploring the Dataset (SQuAD) in Python.mp4
- 39.85 MB
17. Train and Evaluate in Python.mp4
- 37.8 MB
4. Using the Tokenizer.mp4
- 34.52 MB
14. Computing Metrics.mp4
- 24.94 MB
11. Question-Answering Metrics in Python.mp4
- 22.88 MB
1. Question-Answering Section Introduction.mp4
- 21.52 MB
2. Exploring the Dataset (SQuAD).mp4
- 20.16 MB
10. Question-Answering Metrics.mp4
- 16.5 MB
18. Question-Answering Section Summary.mp4
- 14.24 MB
16. Train and Evaluate.mp4
- 14.07 MB
12. From Logits to Answers.srt
- 27.71 KB
6. Aligning the Targets.srt
- 19.33 KB
7. Aligning the Targets in Python.srt
- 18.83 KB
13. From Logits to Answers in Python.srt
- 16.89 KB
5. Using the Tokenizer in Python.srt
- 13.08 KB
8. Applying the Tokenizer.srt
- 12.29 KB
9. Applying the Tokenizer in Python.srt
- 12.03 KB
4. Using the Tokenizer.srt
- 10.82 KB
14. Computing Metrics.srt
- 6.62 KB
1. Question-Answering Section Introduction.srt
- 6.11 KB
15. Computing Metrics in Python.srt
- 6.08 KB
2. Exploring the Dataset (SQuAD).srt
- 5.68 KB
18. Question-Answering Section Summary.srt
- 5.04 KB
10. Question-Answering Metrics.srt
- 4.71 KB
17. Train and Evaluate in Python.srt
- 4.67 KB
3. Exploring the Dataset (SQuAD) in Python.srt
- 4.66 KB
16. Train and Evaluate.srt
- 3.32 KB
11. Question-Answering Metrics in Python.srt
- 2.98 KB
GetFreeCourses.Co.url
- 116 B
9. Implement Transformers From Scratch (Advanced)
10. How to Train a Causal Language Model From Scratch.mp4
- 120.37 MB
13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).mp4
- 108.62 MB
12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).mp4
- 95.19 MB
11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).mp4
- 93.99 MB
3. How to Implement Multihead Attention From Scratch.mp4
- 93.41 MB
7. Train and Evaluate Encoder From Scratch.mp4
- 89.33 MB
8. How to Implement Causal Self-Attention From Scratch.mp4
- 39.2 MB
5. How to Implement Positional Encoding From Scratch.mp4
- 35.87 MB
9. How to Implement a Transformer Decoder (GPT) From Scratch.mp4
- 27.3 MB
6. How to Implement Transformer Encoder From Scratch.mp4
- 27.03 MB
1. Implementation Section Introduction.mp4
- 25.6 MB
2. Encoder Implementation Plan & Outline.mp4
- 23.02 MB
4. How to Implement the Transformer Block From Scratch.mp4
- 14.94 MB
14. Implementation Section Summary.mp4
- 10.59 MB
10. How to Train a Causal Language Model From Scratch.srt
- 20.12 KB
13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).srt
- 17.47 KB
3. How to Implement Multihead Attention From Scratch.srt
- 15.5 KB
12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).srt
- 14.97 KB
11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).srt
- 13.39 KB
7. Train and Evaluate Encoder From Scratch.srt
- 12.3 KB
1. Implementation Section Introduction.srt
- 8.49 KB
2. Encoder Implementation Plan & Outline.srt
- 8.37 KB
5. How to Implement Positional Encoding From Scratch.srt
- 6.26 KB
8. How to Implement Causal Self-Attention From Scratch.srt
- 5.68 KB
9. How to Implement a Transformer Decoder (GPT) From Scratch.srt
- 4.86 KB
6. How to Implement Transformer Encoder From Scratch.srt
- 4.82 KB
4. How to Implement the Transformer Block From Scratch.srt
- 2.36 KB
14. Implementation Section Summary.srt
- 1.99 KB
5. Named Entity Recognition (NER) and POS Tagging (Intermediate)
14. POS Tagging & Custom Datasets (Solution).mp4
- 115.13 MB
6. Target Alignment (Code).mp4
- 61.65 MB
4. Target Alignment (Code Preparation).mp4
- 43.02 MB
3. Data & Tokenizer (Code).mp4
- 42.75 MB
10. Metrics (Code).mp4
- 39.34 MB
1. Token Classification Section Introduction.mp4
- 35.82 MB
9. Metrics (Code Preparation).mp4
- 33.44 MB
12. Model and Trainer (Code).mp4
- 22.18 MB
7. Data Collator (Code Preparation).mp4
- 22.1 MB
13. POS Tagging & Custom Datasets (Exercise Prompt).mp4
- 21.33 MB
2. Data & Tokenizer (Code Preparation).mp4
- 19.34 MB
5. Create Tokenized Dataset (Code Preparation).mp4
- 18.34 MB
8. Data Collator (Code).mp4
- 16.94 MB
11. Model and Trainer (Code Preparation).mp4
- 10.79 MB
15. Token Classification Section Summary.mp4
- 8.04 MB
14. POS Tagging & Custom Datasets (Solution).srt
- 17.9 KB
4. Target Alignment (Code Preparation).srt
- 13.76 KB
6. Target Alignment (Code).srt
- 11.86 KB
1. Token Classification Section Introduction.srt
- 9.59 KB
3. Data & Tokenizer (Code).srt
- 9.2 KB
9. Metrics (Code Preparation).srt
- 9.13 KB
13. POS Tagging & Custom Datasets (Exercise Prompt).srt
- 6.85 KB
2. Data & Tokenizer (Code Preparation).srt
- 6.81 KB
10. Metrics (Code).srt
- 6.09 KB
5. Create Tokenized Dataset (Code Preparation).srt
- 5 KB
7. Data Collator (Code Preparation).srt
- 4.92 KB
8. Data Collator (Code).srt
- 3.7 KB
12. Model and Trainer (Code).srt
- 3.12 KB
11. Model and Trainer (Code Preparation).srt
- 2.91 KB
15. Token Classification Section Summary.srt
- 2.6 KB
13. Effective Learning Strategies for Machine Learning FAQ
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
- 108.17 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
- 79.66 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
- 38.96 MB
1. How to Succeed in this Course (Long Version).mp4
- 17.87 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
- 32.69 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
- 23.93 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
- 17.14 KB
1. How to Succeed in this Course (Long Version).srt
- 14.55 KB
GetFreeCourses.Co.url
- 116 B
3. Beginner's Corner
4. Sentiment Analysis in Python.mp4
- 97.05 MB
18. Zero-Shot Classification in Python.mp4
- 87.61 MB
6. Text Generation in Python.mp4
- 86.35 MB
2. From RNNs to Attention and Transformers - Intuition.mp4
- 78.2 MB
10. Named Entity Recognition (NER) in Python.mp4
- 70.24 MB
7. Masked Language Modeling (Article Spinner).mp4
- 67.29 MB
8. Masked Language Modeling (Article Spinner) in Python.mp4
- 67.09 MB
14. Neural Machine Translation in Python.mp4
- 64.1 MB
5. Text Generation.mp4
- 57.1 MB
3. Sentiment Analysis.mp4
- 53.6 MB
1. Beginner's Corner Section Introduction.mp4
- 49.75 MB
16. Question Answering in Python.mp4
- 48.15 MB
12. Text Summarization in Python.mp4
- 45.47 MB
15. Question Answering.mp4
- 40.1 MB
17. Zero-Shot Classification.mp4
- 30.12 MB
13. Neural Machine Translation.mp4
- 28.1 MB
20. Suggestion Box.mp4
- 27.17 MB
11. Text Summarization.mp4
- 24.15 MB
19. Beginner's Corner Section Summary.mp4
- 23.18 MB
9. Named Entity Recognition (NER).mp4
- 22.02 MB
2. From RNNs to Attention and Transformers - Intuition.srt
- 24.01 KB
4. Sentiment Analysis in Python.srt
- 21.12 KB
18. Zero-Shot Classification in Python.srt
- 16.41 KB
7. Masked Language Modeling (Article Spinner).srt
- 16.12 KB
5. Text Generation.srt
- 15.45 KB
1. Beginner's Corner Section Introduction.srt
- 15.06 KB
6. Text Generation in Python.srt
- 14.92 KB
3. Sentiment Analysis.srt
- 14.55 KB
15. Question Answering.srt
- 10.03 KB
14. Neural Machine Translation in Python.srt
- 9.72 KB
10. Named Entity Recognition (NER) in Python.srt
- 9.63 KB
8. Masked Language Modeling (Article Spinner) in Python.srt
- 9.24 KB
13. Neural Machine Translation.srt
- 8.15 KB
17. Zero-Shot Classification.srt
- 7.6 KB
12. Text Summarization in Python.srt
- 7.55 KB
11. Text Summarization.srt
- 7.08 KB
16. Question Answering in Python.srt
- 6.97 KB
19. Beginner's Corner Section Summary.srt
- 6.39 KB
9. Named Entity Recognition (NER).srt
- 6.24 KB
20. Suggestion Box.srt
- 4.82 KB
12. Extra Help With Python Coding for Beginners FAQ
1. How to Code by Yourself (part 1).mp4
- 71.84 MB
3. Proof that using Jupyter Notebook is the same as not using it.mp4
- 69.42 MB
2. How to Code by Yourself (part 2).mp4
- 49.14 MB
1. How to Code by Yourself (part 1).srt
- 23.13 KB
3. Proof that using Jupyter Notebook is the same as not using it.srt
- 14.92 KB
2. How to Code by Yourself (part 2).srt
- 13.24 KB
8. Transformers and Attention Theory (Advanced)
3. Self-Attention & Scaled Dot-Product Attention.mp4
- 64.27 MB
10. Decoder Architecture.mp4
- 49.61 MB
11. Encoder-Decoder Architecture.mp4
- 39.7 MB
2. Basic Self-Attention.mp4
- 36.97 MB
6. Multi-Head Attention.mp4
- 33.71 MB
13. GPT.mp4
- 31.17 MB
14. GPT-2.mp4
- 29.67 MB
7. Transformer Block.mp4
- 29.5 MB
8. Positional Encodings.mp4
- 29.03 MB
9. Encoder Architecture.mp4
- 25.21 MB
15. GPT-3.mp4
- 23.99 MB
12. BERT.mp4
- 23.25 MB
4. Attention Efficiency.mp4
- 21.57 MB
16. Theory Section Summary.mp4
- 21 MB
1. Theory Section Introduction.mp4
- 17.14 MB
5. Attention Mask.mp4
- 15.11 MB
3. Self-Attention & Scaled Dot-Product Attention.srt
- 23.94 KB
10. Decoder Architecture.srt
- 14.61 KB
2. Basic Self-Attention.srt
- 12.44 KB
11. Encoder-Decoder Architecture.srt
- 11.36 KB
7. Transformer Block.srt
- 9.53 KB
8. Positional Encodings.srt
- 9.46 KB
6. Multi-Head Attention.srt
- 9.35 KB
13. GPT.srt
- 8.65 KB
9. Encoder Architecture.srt
- 8.63 KB
14. GPT-2.srt
- 8.27 KB
1. Theory Section Introduction.srt
- 6.88 KB
15. GPT-3.srt
- 6.57 KB
16. Theory Section Summary.srt
- 6.29 KB
12. BERT.srt
- 6.12 KB
4. Attention Efficiency.srt
- 5.86 KB
5. Attention Mask.srt
- 5.04 KB
2. Getting Setup
2. How to use Github & Extra Coding Tips (Optional).mp4
- 63.9 MB
1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4
- 43.55 MB
5. How to Succeed in This Course.mp4
- 41.19 MB
4. Are You Beginner, Intermediate, or Advanced All are OK!.mp4
- 26.74 MB
3. Where to get the code, notebooks, and data.mp4
- 17.77 MB
2. How to use Github & Extra Coding Tips (Optional).srt
- 15.71 KB
5. How to Succeed in This Course.srt
- 13.03 KB
1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt
- 11.99 KB
4. Are You Beginner, Intermediate, or Advanced All are OK!.srt
- 7.14 KB
3. Where to get the code, notebooks, and data.srt
- 4.29 KB
1.1 Data Links.html
- 157 B
3.2 Data Links.html
- 157 B
1.2 Github Link.html
- 145 B
3.3 Github Link.html
- 145 B
3.1 Code Link.html
- 125 B
11. Setting Up Your Environment FAQ
1. Anaconda Environment Setup.mp4
- 52.64 MB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
- 43.61 MB
1. Anaconda Environment Setup.srt
- 20.13 KB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
- 15.81 KB
GetFreeCourses.Co.url
- 116 B
6. Seq2Seq and Neural Machine Translation (Intermediate)
7. Model Inputs (Code).mp4
- 51.41 MB
9. Translation Metrics (BLEU Score & BERT Score) (Code).mp4
- 43.32 MB
5. Aside Seq2Seq Basics (Optional).mp4
- 37.06 MB
11. Train & Evaluate (Code).mp4
- 35.74 MB
4. Data & Tokenizer (Code).mp4
- 34.12 MB
6. Model Inputs (Code Preparation).mp4
- 32.41 MB
2. Data & Tokenizer (Code Preparation).mp4
- 24.53 MB
10. Train & Evaluate (Code Preparation).mp4
- 21.27 MB
8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).mp4
- 19.28 MB
1. Translation Section Introduction.mp4
- 18.2 MB
12. Translation Section Summary.mp4
- 9.77 MB
3. Things Move Fast.mp4
- 6.09 MB
5. Aside Seq2Seq Basics (Optional).srt
- 15.25 KB
6. Model Inputs (Code Preparation).srt
- 11.21 KB
7. Model Inputs (Code).srt
- 7.78 KB
2. Data & Tokenizer (Code Preparation).srt
- 7.5 KB
4. Data & Tokenizer (Code).srt
- 6.44 KB
1. Translation Section Introduction.srt
- 6.35 KB
9. Translation Metrics (BLEU Score & BERT Score) (Code).srt
- 6.33 KB
10. Train & Evaluate (Code Preparation).srt
- 5.62 KB
8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).srt
- 4.96 KB
11. Train & Evaluate (Code).srt
- 4.64 KB
12. Translation Section Summary.srt
- 3.3 KB
3. Things Move Fast.srt
- 2.36 KB
1. Welcome
2. Outline.mp4
- 50.65 MB
1. Introduction.mp4
- 34.6 MB
2. Outline.srt
- 13.51 KB
1. Introduction.srt
- 5.63 KB
14. Appendix FAQ Finale
2. BONUS.mp4
- 39.92 MB
1. What is the Appendix.mp4
- 16.37 MB
2. BONUS.srt
- 7.94 KB
1. What is the Appendix.srt
- 3.88 KB
10. Extras
1. Data Links.html
- 256 B
How you can help GetFreeCourses.Co.txt
- 182 B
Download Paid Udemy Courses For Free.url
- 116 B
GetFreeCourses.Co.url
- 116 B
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InfoHash:
0C83610B6BD36929682B5042A3507E6C15D4ADE3
Last updated:
Aug 26, 2023
File count:
267 B
File Category:
1
Tags:
getfreecourses, udemy, data, science, transformers, natural, language, processing
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