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      • Introduction
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      • Introduction
        • Introduction
          • Introduction
            • 1-Introduction
              • 5-Machine-Learning-Basics
              • 5.1-Learning-Algorithms
                • Pattern-recognition
                  • Sequence-labeling
                  • Sequence-Labeling-Generative-and-Discriminative
              • 5.2-Capacity-Overfitting-and-Underfitting
                • Hyperparameter(machine-learning)
                • Cross-validation(statistics)
                • 5.4-Estimators-Bias-and-Variance
                • Bias–variance tradeoff
                • 5.5-Maximum-Likelihood-Estimation
            • Part-II-Deep-Networksb-Modern-Practice
              • 6-Deep-Feedforward-Network
              • 6.2-Gradient-Based-Learning
                • 6.4-Architecture-Design
                • Universal-approximation-theorem
                • Introduction
                  • Introduction
                  • zhihu-Back-Propagation
                  • wikipedia-Backpropagation
                • 6.5-Back-Propagation-and-Other-Differentiation
                • Implementation
                • Backpropagation-through-time
              • 7.8-Early-Stopping
              • 8-Optimization-for-Training-Deep-Models
                • 5.9-Stochastic-Gradient-Descent
                • Gradient-descent
                • Stochastic-gradient-descent
              • 9-Convolutional-Networks
              • 9.3-Pooling
                • Introduction
                • Convolutional-Neural-Networks(CNNs-or-ConvNets)
              • CNN-translation-invariance
              • CNN-pooling-layer
                • VGG
                • AlexNet
              • Fei-Fei-Li
              • ImageNet
              • paper-Convolutional-Sequence-to-Sequence-Learning
              • 10-Sequence-Modeling-Recurrentand-Recursive-Nets
              • 10.1-Unfolding-Computational-Graphs
              • 10.3-Bidirectional-RNNs
              • 10.4-Encoder-Decoder-Sequence-to-Sequence-Architectures
              • 10.10-The-Long-Short-Term-Memory-and-Other-Gated
                • LSTM
                • colah-Understanding-LSTM-Networks
                • RNN-and-LSTM-tutorial
                • Introduction
                • 12.4.5-Neural-Machine-Translation
          • Introduction
            • Artificial-neural-network
            • Neural-Networks-Tutorial
            • ujjwalkarn-A-Quick-Introduction-to-Neural-Networks
            • Introduction
            • Computational-graph
            • Model-capacity
            • Model-initialization
            • Buzz-word-batch-size
            • Batch-VS-epoch
            • Steps-VS-epochs
            • Word-epoch
            • Activation-function
            • ReLU-VS-sigmoid-VS-softmax
            • sigmoid-in-deep-learning
          • Design-neural-network
            • Introduction
            • End-to-end-reinforcement-learning
            • Papers
        • Data-transformation(statistics)
        • Feature-scaling
        • Normalization(statistics)
        • Introduction
          • Markov-chain
          • Markov-models
          • Hidden-Markov-model
          • Viterbi-algorithm
          • Forward-algorithm
          • CRF
      • Data-generating-process
      • VS-statistical-model-VS-machine-learning-model
      • VS-statistics-model-VS-stochastic-process
        • Introduction
        • Symbolic-and-imperative
        • Introduction
        • Doc
          • Introduction
            • Introduction
            • whitepaper2015
            • Introduction
            • Introduction
          • Introduction
            • Introduction
            • Core-graph-data-structures
              • Introduction
              • tf.control_dependencies
                • Introduction
                • How-to-understand-tf.Variable
            • Introduction
        • paper-Automatic-differentiation-in-PyTorch
        • intro-Keras
        • Getting-started-with-the-Keras-Sequential-model
        • keras-Layers-Convolutional-Layers
      • VS-pytorch-vs-tensorflow
      • Introduction
        • Introduction
        • NLP
        • WordNet
          • Task-of-NLP
            • Entity-Linking
            • Relationship-Extraction
            • Shallow-parsing
            • Text-Classification
            • paper-Bidirectional-LSTM-with-attention-mechanism-and-convolutional-layer
            • Introduction
            • Neural-machine-translation
            • Distant-supervision
          • Representation-of-image-VS--word
          • Introduction
          • Part-of-speech
            • BERT
            • BERT-paper
            • BERT-implementation
            • openai-GPT-2
            • BERT
            • BERT-paper
            • BERT-implementation
            • openai-GPT-2
          • Introduction
        • Introduction
        • Sequence
        • Introduction

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