Deep Learning with PyTorch

  1. Recurrent Neural Networks (RNNs) for Sequential Data
    1. Sequential Data Processing
      1. Types of Sequential Data
        1. Time Series Data
          1. Text and Language Data
            1. Audio and Speech Data
              1. Video Data
              2. Sequence Modeling Challenges
                1. Variable Length Sequences
                  1. Long-term Dependencies
                    1. Temporal Patterns
                  2. Text Processing Fundamentals
                    1. Text Preprocessing
                      1. Tokenization
                        1. Lowercasing and Cleaning
                          1. Stop Word Removal
                          2. Text Representation
                            1. One-hot Encoding
                              1. Word Embeddings
                                1. Word2Vec
                                  1. GloVe
                                    1. FastText
                                    2. Embedding Layers in PyTorch
                                      1. nn.Embedding
                                        1. Pre-trained Embeddings
                                      2. Vocabulary Management
                                        1. Vocabulary Building
                                          1. Unknown Token Handling
                                            1. Subword Tokenization
                                          2. RNN Fundamentals
                                            1. Recurrent Architecture
                                              1. Hidden State Concept
                                                1. Temporal Unrolling
                                                  1. Parameter Sharing Across Time
                                                  2. RNN Forward Pass
                                                    1. State Update Equations
                                                      1. Output Generation
                                                      2. RNN Backward Pass
                                                        1. Backpropagation Through Time
                                                          1. Gradient Flow
                                                          2. Vanishing and Exploding Gradients
                                                            1. Gradient Vanishing Problem
                                                              1. Gradient Exploding Problem
                                                                1. Gradient Clipping
                                                              2. Advanced RNN Architectures
                                                                1. Long Short-Term Memory (LSTM)
                                                                  1. LSTM Cell Architecture
                                                                    1. Forget Gate
                                                                      1. Input Gate
                                                                        1. Output Gate
                                                                          1. Cell State Management
                                                                            1. Bidirectional LSTM
                                                                            2. Gated Recurrent Unit (GRU)
                                                                              1. GRU Cell Architecture
                                                                                1. Update Gate
                                                                                  1. Reset Gate
                                                                                    1. Simplified Gating Mechanism
                                                                                  2. RNN Implementation in PyTorch
                                                                                    1. Basic RNN Layers
                                                                                      1. nn.RNN Configuration
                                                                                        1. Input and Output Shapes
                                                                                        2. LSTM Implementation
                                                                                          1. nn.LSTM Configuration
                                                                                            1. Hidden and Cell States
                                                                                            2. GRU Implementation
                                                                                              1. nn.GRU Configuration
                                                                                              2. Sequence Handling
                                                                                                1. Variable Length Sequences
                                                                                                  1. Padding and Packing
                                                                                                    1. pad_sequence
                                                                                                      1. pack_padded_sequence
                                                                                                        1. pad_packed_sequence
                                                                                                      2. Many-to-One Architecture
                                                                                                        1. Sequence Classification
                                                                                                          1. Sentiment Analysis
                                                                                                          2. Many-to-Many Architecture
                                                                                                            1. Sequence-to-Sequence
                                                                                                              1. Language Modeling
                                                                                                              2. One-to-Many Architecture
                                                                                                                1. Sequence Generation
                                                                                                              3. Time Series Processing
                                                                                                                1. Time Series Preprocessing
                                                                                                                  1. Normalization
                                                                                                                    1. Windowing
                                                                                                                      1. Feature Engineering
                                                                                                                      2. Forecasting Models
                                                                                                                        1. Univariate Forecasting
                                                                                                                          1. Multivariate Forecasting
                                                                                                                            1. Multi-step Prediction

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                                                                                                                        6. Convolutional Neural Networks (CNNs) for Computer Vision

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                                                                                                                        8. Advanced Deep Learning Architectures