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Analysis of the LSTM principle of NLP

Article directory background Limitations of simpleRNN LSTM Write a sigmoid example by hand Neural networks supporting long memory Interpretation of the three gates Background SimpleRNN has certain limitations, Text on image: The picture title mentions “SimpleRNN is a basic model. It is used to solve sequential problems, in which the output of each step will […]

LSTM and BiLSTM of NLP

Article directory Code display Code interpretation Introduction to Bidirectional LSTM (BiLSTM) Code display import pandas as pd import tensorflow astf tf.random.set_seed(1) df = pd.read_csv(“../data/Clothing Reviews.csv”) print(df.info()) df[‘Review Text’] = df[‘Review Text’].astype(str) x_train = df[‘Review Text’] y_train = df[‘Rating’] print(y_train.unique()) <class ‘pandas.core.frame.DataFrame’> RangeIndex: 23486 entries, 0 to 23485 Data columns (total 11 columns): # Column Non-Null […]

GJO-LSTM-Adaboost optimizes Adaboost classification prediction of long short-term memory neural network LSTM based on the golden jackal algorithm

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[Wind Power Forecast] Based on convolutional neural network combined with long short memory network CNN-LSTM to realize wind power power multi-input single-output regression prediction with matlab code

Based on convolutional neural network combined with long short memory network CNN-LSTM to realize wind power power multi-input single-output regression prediction with matlab code

CNN-LSTM is based on convolutional neural network-long short-term memory network time series prediction Matlab

[Wind power prediction] Optimizing the convolutional neural network based on the ocean predation algorithm combined with the long short memory network MPA-CNN-LSTM to realize multi-input single-output regression prediction of wind power power with matlab code

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Practical combat of entity recognition based on bert+bilstm+crf based on torch framework

First, we need to import the required libraries: import torch import torch.nn as nn import torch.optim as optim from transformers import BertTokenizer, BertModel Then define some hyperparameters and model structure: # Hyperparameters MAX_LEN = 128 BATCH_SIZE = 32 EPOCHS = 10 LEARNING_RATE = 0.001 # Load BERT model and tokenizer tokenizer = BertTokenizer.from_pretrained(‘bert-base-chinese’) bert_model = […]

[Load Forecasting] Power system load forecasting algorithm based on GA-LSTM genetic optimization long short memory network (Matlab code implementation)…

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For cooperation on MATLAB projects, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization content, click Intelligent optimization algorithm […]

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