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______________ means the gradient of deep learning models du…

______________ means the gradient of deep learning models during training is too small or too large (unstable) ; therefore, the deep learning model cannot learn more effectively. To mitigate this problem, we can use the ReLU function as an activation function, use gradient clipping to normalize it when the norm of the gradient is larger than the threshold, and add gate structures in the deep learning model to consider long-term dependency in the dataset.

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Ref: https://huggingface.co/learn/nlp-course  Parallel compu…

Ref: https://huggingface.co/learn/nlp-course  Parallel computation is applicable for transformer model; therefore, it is easy to increase the size of the model with a larger corpus data. Language model (LM) and large language model (LLM) are mostly based on transformer model. LM is divided into three groups: encoder-only model, decoder-only model, and encoder-decoder model. For example, the Bidirectional Encoder Representations from Transformers (BERT) model can be used to generate embedding vectors from text data for text classification, because BERT is (1)__________________( a. encoder-only model, b. decoder-only model). For example, OpenAI’s ChatGPT is based on Generative Pre-trained Transformer (GPT) 4 and 4.5. GPT models are more suitable for text generation in diverse tasks, because GPT is a (2)__________________( a. encoder-only model, b. decoder-only model).

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A convolutional neural network (CNN) is widely used for text…

A convolutional neural network (CNN) is widely used for text and image classification. CNN models contain a convolutional and pooling layer. A convolutional layer have (1)___________ for a convolutional operation as follows: (2)__________ determines the number of pixels by which we move (1)_________ across the input matrix as follows: (3)_________ is adding a boundary around the input matrix to preserve the size of the matrix in the output as follows:   Ref: https://github.com/WegraLee/deep-learning-from-scratch?tab=readme-ov-file Please select the right answer _________________ for (1), (2), and (3)      

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Ref: https://github.com/WegraLee/deep-learning-from-scratch-…

Ref: https://github.com/WegraLee/deep-learning-from-scratch-2 The above figure shows the structure of ____________ model and read line indicates the backpropagation flow. This model has an input, hidden, and output layer. The hidden layer contains a memory cell with three gates: input gate, forget gate, and output gate. By adding gate structures in a memory cell, this model can consider long-term dependencies from long-sequence data.

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The structure of _________ model for the image classificatio…

The structure of _________ model for the image classification is: Ref: https://github.com/WegraLee/deep-learning-from-scratch?tab=readme-ov-file An affine layer (i.e., a fully connected layer) means each input node in a layer is connected to all output nodes in the next layer. Ref: https://ml4a.github.io/ml4a/neural_networks As can be seen in the above figure, the deep learning model can classify the image dataset from zero to nine. First, input image data is converted to a 2-dimensional matrix (28 rows x 28 columns = 768 pixels). Second, the 2-dimensional matrix is converted into a vector for 768-pixels. If the first fully connected layer (i.e., affine layer) has 100 hidden nodes, there will be 76,800 connections. In this case, 76,800 parameters for weights and 76,800 parameters for constant terms are required to be estimated during the training step. As a result, this deep learning model requires high computational resources and time.

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(1)________________(a. pre-training b. fine-tuning, c. hyper…

(1)________________(a. pre-training b. fine-tuning, c. hyperparameter-tuning d. overfitting; 5 points): using a pre-trained language model with a large corpus and does additional training with your dataset for a specific task. It requires relatively low computation and data resources but generally performs well. (2)________________(a. pre-training b. fine-tuning, c. hyperparameter-tuning d. overfitting; 5 points): is training the model with a large corpus from scratch; however, this approach requires high computational resources and big corpus data.

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Please label B.   

Please label B.   

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Which one separates the upper and lower respiratory tracts? …

Which one separates the upper and lower respiratory tracts?   

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Olfactory nerve is a Cranial Nerve ___.

Olfactory nerve is a Cranial Nerve ___.

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Which of the following is the primary muscle contributing to…

Which of the following is the primary muscle contributing to the inhalation?

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