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Please note that this page does not hosts or makes available any of the listed filenames. You
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| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [FreeCourseSite.com].url |
127B |
| [FreeCourseSite.com].url |
127B |
| [FreeCourseSite.com].url |
127B |
| [FreeCourseSite.com].url |
127B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| 1.1 Data Links.html |
157B |
| 1.2 Github Link.html |
145B |
| 1. Anaconda Environment Setup.mp4 |
52.64MB |
| 1. Anaconda Environment Setup.srt |
20.13KB |
| 1. Beginner's Corner Section Introduction.mp4 |
49.75MB |
| 1. Beginner's Corner Section Introduction.srt |
15.06KB |
| 1. Data Links.html |
256B |
| 1. Fine-Tuning Section Introduction.mp4 |
20.16MB |
| 1. Fine-Tuning Section Introduction.srt |
6.14KB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 |
43.55MB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt |
11.99KB |
| 1. How to Code by Yourself (part 1).mp4 |
71.84MB |
| 1. How to Code by Yourself (part 1).srt |
23.13KB |
| 1. How to Succeed in this Course (Long Version).mp4 |
17.87MB |
| 1. How to Succeed in this Course (Long Version).srt |
14.55KB |
| 1. Implementation Section Introduction.mp4 |
25.60MB |
| 1. Implementation Section Introduction.srt |
8.49KB |
| 1. Introduction.mp4 |
34.60MB |
| 1. Introduction.srt |
5.63KB |
| 1. Question-Answering Section Introduction.mp4 |
21.52MB |
| 1. Question-Answering Section Introduction.srt |
6.11KB |
| 1. Theory Section Introduction.mp4 |
17.14MB |
| 1. Theory Section Introduction.srt |
6.88KB |
| 1. Token Classification Section Introduction.mp4 |
35.82MB |
| 1. Token Classification Section Introduction.srt |
9.59KB |
| 1. Translation Section Introduction.mp4 |
18.20MB |
| 1. Translation Section Introduction.srt |
6.35KB |
| 1. What is the Appendix.mp4 |
16.37MB |
| 1. What is the Appendix.srt |
3.88KB |
| 10. Decoder Architecture.mp4 |
49.61MB |
| 10. Decoder Architecture.srt |
14.61KB |
| 10. Fine-Tuning Transformers with Custom Dataset.mp4 |
106.85MB |
| 10. Fine-Tuning Transformers with Custom Dataset.srt |
15.10KB |
| 10. How to Train a Causal Language Model From Scratch.mp4 |
120.37MB |
| 10. How to Train a Causal Language Model From Scratch.srt |
20.12KB |
| 10. Metrics (Code).mp4 |
39.34MB |
| 10. Metrics (Code).srt |
6.09KB |
| 10. Named Entity Recognition (NER) in Python.mp4 |
70.24MB |
| 10. Named Entity Recognition (NER) in Python.srt |
9.63KB |
| 10. Question-Answering Metrics.mp4 |
16.50MB |
| 10. Question-Answering Metrics.srt |
4.71KB |
| 10. Train & Evaluate (Code Preparation).mp4 |
21.27MB |
| 10. Train & Evaluate (Code Preparation).srt |
5.62KB |
| 11. Encoder-Decoder Architecture.mp4 |
39.70MB |
| 11. Encoder-Decoder Architecture.srt |
11.36KB |
| 11. Hugging Face AutoConfig.mp4 |
40.86MB |
| 11. Hugging Face AutoConfig.srt |
6.03KB |
| 11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).mp4 |
93.99MB |
| 11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).srt |
13.39KB |
| 11. Model and Trainer (Code Preparation).mp4 |
10.79MB |
| 11. Model and Trainer (Code Preparation).srt |
2.91KB |
| 11. Question-Answering Metrics in Python.mp4 |
22.88MB |
| 11. Question-Answering Metrics in Python.srt |
2.98KB |
| 11. Text Summarization.mp4 |
24.15MB |
| 11. Text Summarization.srt |
7.08KB |
| 11. Train & Evaluate (Code).mp4 |
35.74MB |
| 11. Train & Evaluate (Code).srt |
4.64KB |
| 12. BERT.mp4 |
23.25MB |
| 12. BERT.srt |
6.12KB |
| 12. Fine-Tuning with Multiple Inputs (Textual Entailment).mp4 |
28.42MB |
| 12. Fine-Tuning with Multiple Inputs (Textual Entailment).srt |
10.32KB |
| 12. From Logits to Answers.mp4 |
95.56MB |
| 12. From Logits to Answers.srt |
27.71KB |
| 12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).mp4 |
95.19MB |
| 12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).srt |
14.97KB |
| 12. Model and Trainer (Code).mp4 |
22.18MB |
| 12. Model and Trainer (Code).srt |
3.12KB |
| 12. Text Summarization in Python.mp4 |
45.47MB |
| 12. Text Summarization in Python.srt |
7.55KB |
| 12. Translation Section Summary.mp4 |
9.77MB |
| 12. Translation Section Summary.srt |
3.30KB |
| 13. Fine-Tuning Transformers with Multiple Inputs in Python.mp4 |
56.66MB |
| 13. Fine-Tuning Transformers with Multiple Inputs in Python.srt |
6.62KB |
| 13. From Logits to Answers in Python.mp4 |
120.62MB |
| 13. From Logits to Answers in Python.srt |
16.89KB |
| 13. GPT.mp4 |
31.17MB |
| 13. GPT.srt |
8.65KB |
| 13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).mp4 |
108.62MB |
| 13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).srt |
17.47KB |
| 13. Neural Machine Translation.mp4 |
28.10MB |
| 13. Neural Machine Translation.srt |
8.15KB |
| 13. POS Tagging & Custom Datasets (Exercise Prompt).mp4 |
21.33MB |
| 13. POS Tagging & Custom Datasets (Exercise Prompt).srt |
6.85KB |
| 14. Computing Metrics.mp4 |
24.94MB |
| 14. Computing Metrics.srt |
6.62KB |
| 14. Fine-Tuning Section Summary.mp4 |
15.78MB |
| 14. Fine-Tuning Section Summary.srt |
4.11KB |
| 14. GPT-2.mp4 |
29.67MB |
| 14. GPT-2.srt |
8.27KB |
| 14. Implementation Section Summary.mp4 |
10.59MB |
| 14. Implementation Section Summary.srt |
1.99KB |
| 14. Neural Machine Translation in Python.mp4 |
64.10MB |
| 14. Neural Machine Translation in Python.srt |
9.72KB |
| 14. POS Tagging & Custom Datasets (Solution).mp4 |
115.13MB |
| 14. POS Tagging & Custom Datasets (Solution).srt |
17.90KB |
| 15. Computing Metrics in Python.mp4 |
44.26MB |
| 15. Computing Metrics in Python.srt |
6.08KB |
| 15. GPT-3.mp4 |
23.99MB |
| 15. GPT-3.srt |
6.57KB |
| 15. Question Answering.mp4 |
40.10MB |
| 15. Question Answering.srt |
10.03KB |
| 15. Token Classification Section Summary.mp4 |
8.04MB |
| 15. Token Classification Section Summary.srt |
2.60KB |
| 16. Question Answering in Python.mp4 |
48.15MB |
| 16. Question Answering in Python.srt |
6.97KB |
| 16. Theory Section Summary.mp4 |
21.00MB |
| 16. Theory Section Summary.srt |
6.29KB |
| 16. Train and Evaluate.mp4 |
14.07MB |
| 16. Train and Evaluate.srt |
3.32KB |
| 17. Train and Evaluate in Python.mp4 |
37.80MB |
| 17. Train and Evaluate in Python.srt |
4.67KB |
| 17. Zero-Shot Classification.mp4 |
30.12MB |
| 17. Zero-Shot Classification.srt |
7.60KB |
| 18. Question-Answering Section Summary.mp4 |
14.24MB |
| 18. Question-Answering Section Summary.srt |
5.04KB |
| 18. Zero-Shot Classification in Python.mp4 |
87.61MB |
| 18. Zero-Shot Classification in Python.srt |
16.41KB |
| 19. Beginner's Corner Section Summary.mp4 |
23.18MB |
| 19. Beginner's Corner Section Summary.srt |
6.39KB |
| 2. Basic Self-Attention.mp4 |
36.97MB |
| 2. Basic Self-Attention.srt |
12.44KB |
| 2. BONUS.mp4 |
39.92MB |
| 2. BONUS.srt |
7.94KB |
| 2. Data & Tokenizer (Code Preparation).mp4 |
19.34MB |
| 2. Data & Tokenizer (Code Preparation).mp4 |
24.53MB |
| 2. Data & Tokenizer (Code Preparation).srt |
6.81KB |
| 2. Data & Tokenizer (Code Preparation).srt |
7.50KB |
| 2. Encoder Implementation Plan & Outline.mp4 |
23.02MB |
| 2. Encoder Implementation Plan & Outline.srt |
8.37KB |
| 2. Exploring the Dataset (SQuAD).mp4 |
20.16MB |
| 2. Exploring the Dataset (SQuAD).srt |
5.68KB |
| 2. From RNNs to Attention and Transformers - Intuition.mp4 |
78.20MB |
| 2. From RNNs to Attention and Transformers - Intuition.srt |
24.01KB |
| 2. How to Code by Yourself (part 2).mp4 |
49.14MB |
| 2. How to Code by Yourself (part 2).srt |
13.24KB |
| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
43.61MB |
| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt |
15.81KB |
| 2. How to use Github & Extra Coding Tips (Optional).mp4 |
63.90MB |
| 2. How to use Github & Extra Coding Tips (Optional).srt |
15.71KB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
38.96MB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt |
32.69KB |
| 2. Outline.mp4 |
50.65MB |
| 2. Outline.srt |
13.51KB |
| 2. Text Preprocessing and Tokenization Review.mp4 |
63.16MB |
| 2. Text Preprocessing and Tokenization Review.srt |
18.22KB |
| 20. Suggestion Box.mp4 |
27.17MB |
| 20. Suggestion Box.srt |
4.82KB |
| 3.1 Code Link.html |
125B |
| 3.2 Data Links.html |
157B |
| 3.3 Github Link.html |
145B |
| 3. Data & Tokenizer (Code).mp4 |
42.75MB |
| 3. Data & Tokenizer (Code).srt |
9.20KB |
| 3. Exploring the Dataset (SQuAD) in Python.mp4 |
39.85MB |
| 3. Exploring the Dataset (SQuAD) in Python.srt |
4.66KB |
| 3. How to Implement Multihead Attention From Scratch.mp4 |
93.41MB |
| 3. How to Implement Multihead Attention From Scratch.srt |
15.50KB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 |
79.66MB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt |
17.14KB |
| 3. Models and Tokenizers.mp4 |
64.57MB |
| 3. Models and Tokenizers.srt |
20.60KB |
| 3. Proof that using Jupyter Notebook is the same as not using it.mp4 |
69.42MB |
| 3. Proof that using Jupyter Notebook is the same as not using it.srt |
14.92KB |
| 3. Self-Attention & Scaled Dot-Product Attention.mp4 |
64.27MB |
| 3. Self-Attention & Scaled Dot-Product Attention.srt |
23.94KB |
| 3. Sentiment Analysis.mp4 |
53.60MB |
| 3. Sentiment Analysis.srt |
14.55KB |
| 3. Things Move Fast.mp4 |
6.09MB |
| 3. Things Move Fast.srt |
2.36KB |
| 3. Where to get the code, notebooks, and data.mp4 |
17.77MB |
| 3. Where to get the code, notebooks, and data.srt |
4.29KB |
| 4. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 |
26.74MB |
| 4. Are You Beginner, Intermediate, or Advanced All are OK!.srt |
7.14KB |
| 4. Attention Efficiency.mp4 |
21.57MB |
| 4. Attention Efficiency.srt |
5.86KB |
| 4. Data & Tokenizer (Code).mp4 |
34.12MB |
| 4. Data & Tokenizer (Code).srt |
6.44KB |
| 4. How to Implement the Transformer Block From Scratch.mp4 |
14.94MB |
| 4. How to Implement the Transformer Block From Scratch.srt |
2.36KB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 |
108.17MB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt |
23.93KB |
| 4. Models and Tokenizers in Python.mp4 |
84.26MB |
| 4. Models and Tokenizers in Python.srt |
14.12KB |
| 4. Sentiment Analysis in Python.mp4 |
97.05MB |
| 4. Sentiment Analysis in Python.srt |
21.12KB |
| 4. Target Alignment (Code Preparation).mp4 |
43.02MB |
| 4. Target Alignment (Code Preparation).srt |
13.76KB |
| 4. Using the Tokenizer.mp4 |
34.52MB |
| 4. Using the Tokenizer.srt |
10.82KB |
| 5. Aside Seq2Seq Basics (Optional).mp4 |
37.06MB |
| 5. Aside Seq2Seq Basics (Optional).srt |
15.25KB |
| 5. Attention Mask.mp4 |
15.11MB |
| 5. Attention Mask.srt |
5.04KB |
| 5. Create Tokenized Dataset (Code Preparation).mp4 |
18.34MB |
| 5. Create Tokenized Dataset (Code Preparation).srt |
5.00KB |
| 5. How to Implement Positional Encoding From Scratch.mp4 |
35.87MB |
| 5. How to Implement Positional Encoding From Scratch.srt |
6.26KB |
| 5. How to Succeed in This Course.mp4 |
41.19MB |
| 5. How to Succeed in This Course.srt |
13.03KB |
| 5. Text Generation.mp4 |
57.10MB |
| 5. Text Generation.srt |
15.45KB |
| 5. Transfer Learning & Fine-Tuning (pt 1).mp4 |
59.83MB |
| 5. Transfer Learning & Fine-Tuning (pt 1).srt |
12.69KB |
| 5. Using the Tokenizer in Python.mp4 |
72.13MB |
| 5. Using the Tokenizer in Python.srt |
13.08KB |
| 6. Aligning the Targets.mp4 |
69.08MB |
| 6. Aligning the Targets.srt |
19.33KB |
| 6. How to Implement Transformer Encoder From Scratch.mp4 |
27.03MB |
| 6. How to Implement Transformer Encoder From Scratch.srt |
4.82KB |
| 6. Model Inputs (Code Preparation).mp4 |
32.41MB |
| 6. Model Inputs (Code Preparation).srt |
11.21KB |
| 6. Multi-Head Attention.mp4 |
33.71MB |
| 6. Multi-Head Attention.srt |
9.35KB |
| 6. Target Alignment (Code).mp4 |
61.65MB |
| 6. Target Alignment (Code).srt |
11.86KB |
| 6. Text Generation in Python.mp4 |
86.35MB |
| 6. Text Generation in Python.srt |
14.92KB |
| 6. Transfer Learning & Fine-Tuning (pt 2).mp4 |
49.31MB |
| 6. Transfer Learning & Fine-Tuning (pt 2).srt |
14.58KB |
| 7. Aligning the Targets in Python.mp4 |
103.33MB |
| 7. Aligning the Targets in Python.srt |
18.83KB |
| 7. Data Collator (Code Preparation).mp4 |
22.10MB |
| 7. Data Collator (Code Preparation).srt |
4.92KB |
| 7. Masked Language Modeling (Article Spinner).mp4 |
67.29MB |
| 7. Masked Language Modeling (Article Spinner).srt |
16.12KB |
| 7. Model Inputs (Code).mp4 |
51.41MB |
| 7. Model Inputs (Code).srt |
7.78KB |
| 7. Train and Evaluate Encoder From Scratch.mp4 |
89.33MB |
| 7. Train and Evaluate Encoder From Scratch.srt |
12.30KB |
| 7. Transfer Learning & Fine-Tuning (pt 3).mp4 |
56.66MB |
| 7. Transfer Learning & Fine-Tuning (pt 3).srt |
13.67KB |
| 7. Transformer Block.mp4 |
29.50MB |
| 7. Transformer Block.srt |
9.53KB |
| 8. Applying the Tokenizer.mp4 |
45.05MB |
| 8. Applying the Tokenizer.srt |
12.29KB |
| 8. Data Collator (Code).mp4 |
16.94MB |
| 8. Data Collator (Code).srt |
3.70KB |
| 8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.mp4 |
58.43MB |
| 8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.srt |
16.85KB |
| 8. How to Implement Causal Self-Attention From Scratch.mp4 |
39.20MB |
| 8. How to Implement Causal Self-Attention From Scratch.srt |
5.68KB |
| 8. Masked Language Modeling (Article Spinner) in Python.mp4 |
67.09MB |
| 8. Masked Language Modeling (Article Spinner) in Python.srt |
9.24KB |
| 8. Positional Encodings.mp4 |
29.03MB |
| 8. Positional Encodings.srt |
9.46KB |
| 8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).mp4 |
19.28MB |
| 8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).srt |
4.96KB |
| 9. Applying the Tokenizer in Python.mp4 |
76.50MB |
| 9. Applying the Tokenizer in Python.srt |
12.03KB |
| 9. Encoder Architecture.mp4 |
25.21MB |
| 9. Encoder Architecture.srt |
8.63KB |
| 9. Fine-Tuning Sentiment Analysis in Python.mp4 |
130.77MB |
| 9. Fine-Tuning Sentiment Analysis in Python.srt |
19.29KB |
| 9. How to Implement a Transformer Decoder (GPT) From Scratch.mp4 |
27.30MB |
| 9. How to Implement a Transformer Decoder (GPT) From Scratch.srt |
4.86KB |
| 9. Metrics (Code Preparation).mp4 |
33.44MB |
| 9. Metrics (Code Preparation).srt |
9.13KB |
| 9. Named Entity Recognition (NER).mp4 |
22.02MB |
| 9. Named Entity Recognition (NER).srt |
6.24KB |
| 9. Translation Metrics (BLEU Score & BERT Score) (Code).mp4 |
43.32MB |
| 9. Translation Metrics (BLEU Score & BERT Score) (Code).srt |
6.33KB |