Natural Language Processing Fundamentals Techniques, Tools, and Applications

1. Module 2 Text Processing and Feature Engineering/003. Lesson 2.3 Use Case Who Wrote it Authorship Attribution with Heuristic NLP.mp4 126.99 MB
2. Module 4 Advanced NLP Models/004. Lesson 4.4 Use Case Fine-tuning a Sentiment Analysis Classifier with DistilBERT.mp4 112.85 MB
3. Module 5 Beyond the NLP Model/003. Lesson 5.3 Use Case Build Your Own Retrieval-Augmented Generation (RAG) System.mp4 83.70 MB
4. Module 3 Traditional NLP Models/001. Lesson 3.1 Probabilistic Models.mp4 75.72 MB
5. Module 2 Text Processing and Feature Engineering/002. Lesson 2.2 Feature Engineering Techniques.mp4 68.86 MB
6. Module 4 Advanced NLP Models/003. Lesson 4.3 Large Language Models (LLMs).mp4 62.42 MB
7. Module 2 Text Processing and Feature Engineering/001. Lesson 2.1 Preprocessing Techniques.mp4 61.22 MB
8. Module 3 Traditional NLP Models/003. Lesson 3.3 Use Case Text Classification with Naive Bayes.mp4 59.53 MB
9. Module 3 Traditional NLP Models/002. Lesson 3.2 Introduction to Neural Networks in NLP.mp4 58.98 MB
10. Module 4 Advanced NLP Models/002. Lesson 4.2 Task-Specific Transformer Models and Fine-Tuning.mp4 56.49 MB
11. Module 1 Introduction to Linguistics, NLP and Related Platforms/003. Lesson 1.3 Major Platforms and Packages Used in this Course.mp4 51.49 MB
12. Module 1 Introduction to Linguistics, NLP and Related Platforms/001. Lesson 1.1 What is Linguistics.mp4 48.39 MB
13. Module 1 Introduction to Linguistics, NLP and Related Platforms/002. Lesson 1.2 What is Natural Language Processing.mp4 47.59 MB
14. Module 4 Advanced NLP Models/001. Lesson 4.1 Attention Mechanism and Transformers.mp4 46.29 MB
15. Module 5 Beyond the NLP Model/002. Lesson 5.2 MLOps and LLMOps.mp4 44.95 MB
16. Module 5 Beyond the NLP Model/001. Lesson 5.1 Ethical Considerations.mp4 42.43 MB
17. Module 0 Course Introduction/001. Course Introduction.mp4 29.50 MB
18. Module 5 Beyond the NLP Model/004. Lesson 5.4 Course Closing.mp4 15.29 MB
19. z.nlp-fundamentals-main/0203_heuristic_nlp.ipynb 443 KB
20. z.nlp-fundamentals-main/0404_finetuning_transformers.ipynb 256 KB
21. z.nlp-fundamentals-main/0303_naive_bayes.ipynb 128 KB
22. z.nlp-fundamentals-main/0504_llms_and_rag.ipynb 121 KB
23. z.nlp-fundamentals-main/graphics/rag.png 112 KB
24. z.nlp-fundamentals-main/graphics/transformer_architecture.png 80 KB
25. z.nlp-fundamentals-main/graphics/llm.png 25 KB
26. z.nlp-fundamentals-main/graphics/cosine_similarity.png 22 KB
27. Module 2 Text Processing and Feature Engineering/003. Lesson 2.3 Use Case Who Wrote it Authorship Attribution with Heuristic NLP.en.srt 22 KB
28. Module 4 Advanced NLP Models/004. Lesson 4.4 Use Case Fine-tuning a Sentiment Analysis Classifier with DistilBERT.en.srt 20 KB
29. Module 3 Traditional NLP Models/001. Lesson 3.1 Probabilistic Models.en.srt 20 KB
30. Module 2 Text Processing and Feature Engineering/002. Lesson 2.2 Feature Engineering Techniques.en.srt 20 KB
31. Module 4 Advanced NLP Models/003. Lesson 4.3 Large Language Models (LLMs).en.srt 19 KB
32. Module 2 Text Processing and Feature Engineering/001. Lesson 2.1 Preprocessing Techniques.en.srt 16 KB
33. Module 3 Traditional NLP Models/002. Lesson 3.2 Introduction to Neural Networks in NLP.en.srt 16 KB
34. Module 5 Beyond the NLP Model/003. Lesson 5.3 Use Case Build Your Own Retrieval-Augmented Generation (RAG) System.en.srt 15 KB
35. Module 4 Advanced NLP Models/002. Lesson 4.2 Task-Specific Transformer Models and Fine-Tuning.en.srt 15 KB
36. Module 1 Introduction to Linguistics, NLP and Related Platforms/002. Lesson 1.2 What is Natural Language Processing.en.srt 15 KB
37. Module 5 Beyond the NLP Model/001. Lesson 5.1 Ethical Considerations.en.srt 14 KB
38. Module 1 Introduction to Linguistics, NLP and Related Platforms/001. Lesson 1.1 What is Linguistics.en.srt 13 KB
39. Module 5 Beyond the NLP Model/002. Lesson 5.2 MLOps and LLMOps.en.srt 13 KB
40. Module 3 Traditional NLP Models/003. Lesson 3.3 Use Case Text Classification with Naive Bayes.en.srt 12 KB
41. Module 4 Advanced NLP Models/001. Lesson 4.1 Attention Mechanism and Transformers.en.srt 12 KB
42. Module 1 Introduction to Linguistics, NLP and Related Platforms/003. Lesson 1.3 Major Platforms and Packages Used in this Course.en.srt 7 KB
43. Module 0 Course Introduction/001. Course Introduction.en.srt 7 KB
44. Module 5 Beyond the NLP Model/004. Lesson 5.4 Course Closing.en.srt 3 KB
45. z.nlp-fundamentals-main/README.md 2 KB