Natural Language Processing (NLP)

  1. Word Embeddings and Distributed Representations
    1. Distributional Semantics
      1. Distributional Hypothesis
        1. Context Windows
          1. Co-occurrence Statistics
          2. Matrix Factorization Methods
            1. Latent Semantic Analysis
              1. Non-Negative Matrix Factorization
                1. Pointwise Mutual Information
                2. Neural Word Embeddings
                  1. Word2Vec
                    1. Continuous Bag-of-Words
                      1. Skip-gram Model
                        1. Hierarchical Softmax
                          1. Negative Sampling
                          2. GloVe
                            1. Global Matrix Factorization
                              1. Local Context Windows
                              2. FastText
                                1. Subword Information
                                  1. Character N-grams
                                    1. Out-of-Vocabulary Handling
                                  2. Embedding Evaluation
                                    1. Intrinsic Evaluation
                                      1. Word Similarity Tasks
                                        1. Analogy Tasks
                                          1. Clustering Quality
                                          2. Extrinsic Evaluation
                                            1. Downstream Task Performance
                                              1. Transfer Learning Assessment
                                            2. Advanced Embedding Techniques
                                              1. Contextualized Embeddings
                                                1. Multilingual Embeddings
                                                  1. Domain-Specific Embeddings
                                                    1. Temporal Embeddings

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                                                  5. Feature Representation

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                                                  7. Classical Machine Learning for NLP