Udemy - Modern NLP for AI Engineers and Data Scientists

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1 - NLP Foundations Revisited Engineer View
• 1. 1 1 What Makes NLP Different from Other ML Domains.mp4 (80.7 MB)
• 2. 1 2 Text as Data.mp4 (73.8 MB)
• 3. 1 3 NLP Problem Taxonomy.mp4 (68.9 MB)
10 - NLP Pipelines System Design
• 43. 10 1 End-to-End NLP Pipelines.mp4 (52.2 MB)
• 44. 10 2 NLP in Microservices.mp4 (42.9 MB)
• 45. 10 3 Evaluation Monitoring.mp4 (55.5 MB)
• 46. System Design Architecture Exercises.html (13.4 KB)
11 - Beyond LLMs Hybrid NLP Systems
• 47. 11 1 When NOT to Use LLMs.mp4 (44.9 MB)
• 48. 11 2 LLM Classical NLP.mp4 (53.2 MB)
• 49. 11 3 Failure Modes in LLM-Centric NLP.mp4 (52.0 MB)
• 50. Case-Study Design Decision Exercises.html (13.6 KB)
12 - Ethics, Bias Responsible NLP
• 51. 12 1 Bias in Text Data.mp4 (56.6 MB)
• 52. 12 2 Fairness Explainability.mp4 (59.2 MB)
• 53. 12 3 Privacy-Aware NLP.mp4 (63.7 MB)
• 54. Scenario-Based Audit Policy Exercises.html (14.4 KB)
2 - Text Preprocessing Linguistic Pipelines
• 4. 2 1 Text Cleaning in Production.mp4 (54.0 MB)
• 5. 2 2 Tokenization Strategies.mp4 (64.7 MB)
• 6. 2 3 Stemming vs Lemmatization.mp4 (59.5 MB)
• 7. 2 4 Sentence Segmentation Parsing Basics.mp4 (65.3 MB)
• 8. Hands on Lab.html (14.5 KB)
3 - SECTION 3 Feature Engineering for Classical NLP
• 10. 3 2 TF-IDF Statistical Weighting.mp4 (82.0 MB)
• 11. 3 3 Feature Selection for Text.mp4 (79.4 MB)
• 12. 3 4 Classical NLP Models.mp4 (67.9 MB)
• 13. Hands on Lab Model Evaluation.html (11.6 KB)
• 9. 3 1 Bag-of-Words N-grams.mp4 (78.6 MB)
4 - Word Representations Distributional Semantics
• 14. 4 1 Distributional Hypothesis.mp4 (69.8 MB)
• 15. 4 2 Static Word Embeddings.mp4 (52.0 MB)
• 16. 4 3 Embedding Geometry.mp4 (70.3 MB)
• 17. 4 4 Limitations of Static Embeddings.mp4 (69.4 MB)
• 18. Hands on Lab Visualization Exercise.html (11.7 KB)
5 - Sequence Modeling for NLP
• 19. 5 1 Sequence Learning Fundamentals.mp4 (59.6 MB)
• 20. 5 2 Recurrent Neural Networks.mp4 (62.9 MB)
• 21. 5 3 LSTM GRU for NLP.mp4 (71.1 MB)
• 22. 5 4 Bidirectional Models.mp4 (60.6 MB)
• 23. Hands on Lab.html (11.2 KB)
6 - Attention Transformer Fundamentals Pre-LLM
• 24. 6 1 Attention Mechanism.mp4 (64.9 MB)
• 25. 6 2 Transformer Architecture.mp4 (75.3 MB)
• 26. 6 3 Why Transformers Replaced RNNs.mp4 (66.2 MB)
• 27. 6 4 Transformer Use Without LLMs.mp4 (66.3 MB)
• 28. Hands-On Lab Architecture Reasoning Exercise.html (14.2 KB)
7 - Contextual Embeddings Representation Learning
• 29. 7 1 Contextual Embeddings.mp4 (71.2 MB)
• 30. 7 2 Encoder-Only Models.mp4 (52.5 MB)
• 31. 7 3 Sentence Document Embeddings.mp4 (58.9 MB)
• 32. 7 4 Embedding Evaluation.mp4 (74.6 MB)
• 33. Applied Embedding Lab Evaluation Task.html (13.3 KB)
8 - NLP Tasks in Practice
• 34. 8 1 Text Classification.mp4 (59.6 MB)
• 35. 8 2 Named Entity Recognition NER.mp4 (63.8 MB)
• 36. 8 3 Text Similarity Semantic Search.mp4 (62.8 MB)
• 37. 8 4 Topic Modeling.mp4 (68.0 MB)
• 38. End-to-End Hands-On Mini Projects.html (12.6 KB)
9 - Information Retrieval Search Systems
• 39. 9 1 Classical IR.mp4 (64.7 MB)
• 40. 9 2 Vector Search Semantic Retrieval.mp4 (49.4 MB)
• 41. 9 3 Hybrid Search Systems.mp4 (54.8 MB)
• 42. System-Level Hands-On Lab.html (13.8 KB)
• Bonus Resources.txt (0.1 KB)