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Udemy - NLP to LLMs - Build the Understanding That Lasts

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Udemy - NLP to LLMs - Build the Understanding That Lasts

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Udemy - NLP to LLMs - Build the Understanding That Lasts
Bonus Resources.txt
TXT
102.4 B
Get Bonus Downloads Here.url
URL
204.8 B
~Get Your Files Here !
1 - Text as data
1. Welcome and what this course is for.mp4
MP4
9.7 MB
1. Welcome and what this course is for_en-US.srt
SRT
3.5 KB
2. 01-text-as-data-01-why-text-is-hard.en.pdf
PDF
63 KB
2. Why text is hard, and the NLP task landscape.mp4
MP4
25.5 MB
2. Why text is hard, and the NLP task landscape_en-US.srt
SRT
8 KB
3. 01-text-as-data-02-tokens-bow-tfidf.en.pdf
PDF
92.3 KB
3. Tokens, bag of words, TF-IDF.mp4
MP4
24.5 MB
3. Tokens, bag of words, TF-IDF_en-US.srt
SRT
8.3 KB
4. 01-text-as-data-03-lab-sentiment-baseline.en.pdf
PDF
81.4 KB
4. Lab a sentiment baseline on real reviews.mp4
MP4
22.4 MB
4. Lab a sentiment baseline on real reviews_en-US.srt
SRT
8.1 KB
4. solutions-01-sentiment-baseline-solution.ipynb.bin
BIN
33.5 KB
4. starter-01-sentiment-baseline.ipynb.bin
BIN
29.3 KB
README.md
MD
1.3 KB
scikit_learn_data
20news-bydate_py3.pkz
PKZ
14.6 MB
uci
__MACOSX
_sentiment labelled sentences
204.8 B
sentiment labelled sentences
_.DS_Store
DS_STORE
204.8 B
_imdb_labelled.txt
TXT
204.8 B
_readme.txt
TXT
204.8 B
sentiment labelled sentences
2 - Embeddings
3 - Attention and the Transformer
10. 03-attention-transformer-03-the-full-block.en.pdf
PDF
98.1 KB
10. The full block multi-head, feed-forward, residuals, positions.mp4
MP4
26 MB
10. The full block multi-head, feed-forward, residuals, positions_en-US.srt
SRT
8.6 KB
11. 03-attention-transformer-04-encoder-decoder-families.en.pdf
PDF
57.4 KB
11. Encoder, decoder, or both BERT, GPT and T5.mp4
MP4
29.9 MB
11. Encoder, decoder, or both BERT, GPT and T5_en-US.srt
SRT
8.8 KB
4 - How LLMs are made
12. 04-how-llms-are-made-01-pretraining.en.pdf
PDF
74.9 KB
12. Pretraining objective, data, and scale.mp4
MP4
25.9 MB
12. Pretraining objective, data, and scale_en-US.srt
SRT
8.5 KB
13. 04-how-llms-are-made-02-gpt-lineage.en.pdf
PDF
62.8 KB
13. The GPT lineage as a series of bets.mp4
MP4
27.8 MB
13. The GPT lineage as a series of bets_en-US.srt
SRT
8 KB
14. 04-how-llms-are-made-03-instruction-tuning-rlhf.en.pdf
PDF
89.2 KB
14. Instruction tuning and RLHF.mp4
MP4
28.5 MB
14. Instruction tuning and RLHF_en-US.srt
SRT
9.1 KB
15. 04-how-llms-are-made-04-open-model-world.en.pdf
PDF
65 KB
15. The open-model world.mp4
MP4
29.8 MB
15. The open-model world_en-US.srt
SRT
8.7 KB
5 - Using LLMs well
16. 05-using-llms-well-01-sampling.en.pdf
PDF
70.8 KB
16. The open-model world.mp4
MP4
22.5 MB
16. The open-model world_en-US.srt
SRT
8 KB
17. 05-using-llms-well-02-prompting-in-production.en.pdf
PDF
66 KB
17. Prompting that survives contact with production.mp4
MP4
26.3 MB
17. Prompting that survives contact with production_en-US.srt
SRT
8.1 KB
18. 05-using-llms-well-03-structured-output-tools.en.pdf
PDF
70.7 KB
18. Structured output and tool calling.mp4
MP4
25.3 MB
18. Structured output and tool calling_en-US.srt
SRT
8.4 KB
19. 05-using-llms-well-04-context-cost-latency.en.pdf
PDF
72 KB
19. Context windows, cost, and latency budgets.mp4
MP4
24 MB
19. Context windows, cost, and latency budgets_en-US.srt
SRT
8.5 KB
6 - RAG
20. 06-rag-01-why-rag.en.pdf
PDF
54.6 KB
20. Why RAG knowledge, freshness, and grounding.mp4
MP4
26.4 MB
20. Why RAG knowledge, freshness, and grounding_en-US.srt
SRT
7.8 KB
21. 06-rag-02-chunking-and-retrieval-quality.en.pdf
PDF
64.5 KB
21. Chunking, embedding, and retrieval quality.mp4
MP4
25.2 MB
21. Chunking, embedding, and retrieval quality_en-US.srt
SRT
8.2 KB
22. 06-rag-03-lab-rag-over-documents.en.pdf
PDF
60.2 KB
22. Lab RAG over your own documents.mp4
MP4
24.9 MB
22. Lab RAG over your own documents_en-US.srt
SRT
7.9 KB
22. solutions-06-rag-over-documents-solution.ipynb.bin
BIN
52.5 KB
22. starter-06-rag-over-documents.ipynb.bin
BIN
48.1 KB
7 - Fine-tuning
23. 07-fine-tuning-01-when-to-fine-tune.en.pdf
PDF
52.8 KB
23. When to fine-tune, and the cheaper alternatives.mp4
MP4
37.5 MB
23. When to fine-tune, and the cheaper alternatives_en-US.srt
SRT
9.7 KB
24. 07-fine-tuning-02-lora.en.pdf
PDF
66.9 KB
24. LoRA, the mechanism and the knobs.mp4
MP4
35.4 MB
24. LoRA, the mechanism and the knobs_en-US.srt
SRT
10.9 KB
25. 07-fine-tuning-03-lab-lora-fine-tune.en.pdf
PDF
67.3 KB
25. Lab LoRA fine-tune a small model.mp4
MP4
35.4 MB
25. Lab LoRA fine-tune a small model_en-US.srt
SRT
9.4 KB
25. solutions-07-lora-fine-tune-solution.ipynb.bin
BIN
43.2 KB
25. starter-07-lora-fine-tune.ipynb.bin
BIN
33.4 KB
8 - Evaluation and failure modes
26. 08-evaluation-01-failure-modes.en.pdf
PDF
61.8 KB
26. Hallucination, sycophancy, and other systematic failures.mp4
MP4
36.1 MB
26. Hallucination, sycophancy, and other systematic failures_en-US.srt
SRT
11.3 KB
27. 08-evaluation-02-evals.en.pdf
PDF
59.7 KB
27. Evals golden sets, LLM-as-judge, regression harnesses.mp4
MP4
44.5 MB
27. Evals golden sets, LLM-as-judge, regression harnesses_en-US.srt
SRT
12.3 KB
28. 08-evaluation-03-safety-basics.en.pdf
PDF
59 KB
28. Safety-relevant behaviour injection and leakage basics.mp4
MP4
35.6 MB
28. Safety-relevant behaviour injection and leakage basics_en-US.srt
SRT
9.8 KB
9 - Capstone
29. 09-capstone-01-capstone-classical-vs-llm.en.pdf
PDF
60 KB
29. Capstone classical versus LLM on the same task, measured.mp4
MP4
37.2 MB
29. Capstone classical versus LLM on the same task, measured_en-US.srt
SRT
9.8 KB
29. solutions-09-capstone-classical-vs-llm-solution.ipynb.bin
BIN
49.2 KB
29. starter-09-capstone-classical-vs-llm.ipynb.bin
BIN
36.4 KB
30. 09-capstone-02-keeping-current.en.pdf
PDF
40.8 KB
30. Where the field is going, and keeping current without drowning.mp4
MP4
43.5 MB
30. Where the field is going, and keeping current without drowning_en-US.srt
SRT
10.6 KB
30. c2-next-steps.en.pdf
PDF
29.8 KB
8. 03-attention-transformer-01-problem-attention-solves.en.pdf
PDF
67.2 KB
8. The problem attention solves.mp4
MP4
17.3 MB
8. The problem attention solves_en-US.srt
SRT
6.4 KB
9. 03-attention-transformer-02-self-attention-step-by-step.en.pdf
PDF
85.1 KB
9. Self-attention, step by step with shapes.mp4
MP4
19.6 MB
9. Self-attention, step by step with shapes_en-US.srt
SRT
7.1 KB
5. 02-embeddings-01-counts-to-meaning.en.pdf
PDF
72.2 KB
5. From counts to meaning dense vectors.mp4
MP4
24.4 MB
5. From counts to meaning dense vectors_en-US.srt
SRT
7.7 KB
6. 02-embeddings-02-word2vec-and-friends.en.pdf
PDF
69.9 KB
6. word2vec and friends, briefly.mp4
MP4
28.8 MB
6. word2vec and friends, briefly_en-US.srt
SRT
8.6 KB
7. 02-embeddings-03-lab-search-clustering.en.pdf
PDF
69.6 KB
7. Lab embeddings for search and clustering.mp4
MP4
21.8 MB
7. Lab embeddings for search and clustering_en-US.srt
SRT
7.2 KB
7. solutions-02-search-clustering-solution.ipynb.bin
BIN
33.4 KB
7. starter-02-search-clustering.ipynb.bin
BIN
31.2 KB
DS_Store
6 KB
amazon_cells_labelled.txt
TXT
56.9 KB
imdb_labelled.txt
TXT
83.3 KB
readme.txt
TXT
1 KB
yelp_labelled.txt
TXT
59.9 KB

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