Useful Links
1. Introduction to Natural Language Processing
2. Linguistic Foundations
3. Text Processing and Preprocessing
4. Language Modeling
5. Feature Representation
6. Word Embeddings and Distributed Representations
7. Classical Machine Learning for NLP
8. Deep Learning Foundations
9. Recurrent Neural Networks
10. Attention Mechanisms and Transformers
11. Pre-trained Language Models
12. Core NLP Applications
13. Advanced Topics
14. Evaluation and Benchmarking
15. Ethics and Responsible AI
  1. Computer Science
  2. Artificial Intelligence
  3. Natural Language Processing (NLP)

Natural Language Processing (NLP)

1. Introduction to Natural Language Processing
2. Linguistic Foundations
3. Text Processing and Preprocessing
4. Language Modeling
5. Feature Representation
6. Word Embeddings and Distributed Representations
7. Classical Machine Learning for NLP
8. Deep Learning Foundations
9. Recurrent Neural Networks
10. Attention Mechanisms and Transformers
11. Pre-trained Language Models
12. Core NLP Applications
13. Advanced Topics
14. Evaluation and Benchmarking
15. Ethics and Responsible AI
  1. Evaluation and Benchmarking
    1. Evaluation Metrics
      1. Classification Metrics
        1. Accuracy and Error Rate
          1. Precision and Recall
            1. F1-Score and F-beta
              1. Area Under Curve
              2. Generation Metrics
                1. BLEU and Variants
                  1. ROUGE and Variants
                    1. METEOR
                      1. BERTScore
                        1. Semantic Similarity
                        2. Ranking Metrics
                          1. Mean Average Precision
                            1. Normalized Discounted Cumulative Gain
                              1. Mean Reciprocal Rank
                            2. Human Evaluation
                              1. Annotation Guidelines
                                1. Inter-Annotator Agreement
                                  1. Crowdsourcing
                                    1. Expert Evaluation
                                      1. User Studies
                                      2. Benchmark Datasets
                                        1. General Language Understanding
                                          1. GLUE
                                            1. SuperGLUE
                                              1. XTREME
                                              2. Task-Specific Benchmarks
                                                1. SQuAD for Reading Comprehension
                                                  1. CoNLL for Named Entity Recognition
                                                    1. WMT for Machine Translation
                                                    2. Evaluation Challenges
                                                      1. Dataset Bias
                                                        1. Evaluation Reliability
                                                          1. Metric Limitations

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                                                      15. Ethics and Responsible AI

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