Textual Analysis

  1. Feature Engineering and Text Representation
    1. Vectorization Fundamentals
      1. Converting Text to Numbers
        1. Vector Space Models
          1. Dimensionality Considerations
            1. Sparse vs Dense Representations
            2. Basic Vectorization Methods
              1. One-Hot Encoding
                1. Binary Representation
                  1. Vocabulary Size Limitations
                  2. Frequency-Based Encoding
                    1. Count Vectors
                      1. Normalized Frequencies
                    2. Bag-of-Words Models
                      1. Document-Term Matrix
                        1. Matrix Construction
                          1. Sparse Matrix Representation
                            1. Dimensionality Issues
                              1. Memory Considerations
                              2. Count Vectorization
                                1. Binary vs Count Representation
                                  1. Vocabulary Filtering
                                    1. N-gram Integration
                                  2. Term Frequency-Inverse Document Frequency
                                    1. Term Frequency Calculation
                                      1. Raw Count
                                        1. Log Normalization
                                          1. Double Normalization
                                          2. Inverse Document Frequency
                                            1. IDF Formula Variations
                                              1. Smoothing Techniques
                                              2. TF-IDF Weight Calculation
                                                1. Standard TF-IDF
                                                  1. Normalized TF-IDF
                                                  2. Advantages and Limitations of TF-IDF
                                                    1. Strengths in Information Retrieval
                                                      1. Weaknesses with Semantic Similarity
                                                    2. N-gram Features
                                                      1. Unigrams
                                                        1. Single Word Features
                                                          1. Vocabulary Size Considerations
                                                          2. Bigrams
                                                            1. Two-Word Combinations
                                                              1. Phrase Capture
                                                              2. Trigrams
                                                                1. Three-Word Sequences
                                                                  1. Context Enhancement
                                                                  2. Higher-Order N-grams
                                                                    1. Computational Complexity
                                                                      1. Sparsity Issues
                                                                      2. Applications of N-grams
                                                                        1. Language Modeling
                                                                          1. Text Classification
                                                                            1. Authorship Attribution
                                                                          2. Word Embeddings
                                                                            1. Static 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. Co-occurrence Statistics
                                                                                            1. Training Process
                                                                                            2. FastText
                                                                                              1. Subword Information
                                                                                                1. Out-of-Vocabulary Handling
                                                                                                  1. Character N-grams
                                                                                                2. Contextualized Embeddings
                                                                                                  1. ELMo
                                                                                                    1. Bidirectional LSTM
                                                                                                      1. Context-Dependent Representations
                                                                                                      2. BERT
                                                                                                        1. Transformer Architecture
                                                                                                          1. Pre-training Objectives
                                                                                                            1. Fine-tuning Process
                                                                                                              1. Tokenization in BERT
                                                                                                              2. GPT Models
                                                                                                                1. Autoregressive Language Modeling
                                                                                                                  1. Decoder-Only Architecture
                                                                                                                  2. Comparison of Static and Contextualized Embeddings
                                                                                                                    1. Semantic Richness
                                                                                                                      1. Computational Requirements
                                                                                                                        1. Task Performance
                                                                                                                      2. Embedding Operations
                                                                                                                        1. Vector Arithmetic
                                                                                                                          1. Similarity Calculations
                                                                                                                            1. Analogy Tasks
                                                                                                                            2. Embedding Evaluation
                                                                                                                              1. Intrinsic Evaluation
                                                                                                                                1. Extrinsic Evaluation
                                                                                                                                  1. Bias Detection in Embeddings
                                                                                                                                  2. Embedding Visualization
                                                                                                                                    1. Dimensionality Reduction
                                                                                                                                      1. t-SNE
                                                                                                                                        1. PCA
                                                                                                                                          1. UMAP
                                                                                                                                          2. Interactive Visualization Tools

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                                                                                                                                      2. Data Acquisition and Preprocessing

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                                                                                                                                      4. Core Analysis Techniques and Tasks