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BiLSTM model to predict an internal state when given the external state. Also making it into an API and doing stress tests.

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Kaushal-Bora/StatePredictionModel

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__pycache__
__pycache__
 
 
logs
logs
 
 
README.md
README.md
 
 
app.py
app.py
 
 
bestWeights.keras
bestWeights.keras
 
 
dataset.json
dataset.json
 
 
label_encoder_classes.npy
label_encoder_classes.npy
 
 
locustReport100users.html
locustReport100users.html
 
 
locustfile.py
locustfile.py
 
 
max_length.npy
max_length.npy
 
 
model.ipynb
model.ipynb
 
 
model.png
model.png
 
 
tokenizer.pkl
tokenizer.pkl
 
 

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I have made a BiLSTM DL model for the task. The task requires me to predict the internal state labels when the external state labels are given. The model is giving 99% testing accuracy 99% precision and 100% recall. I have added the tensorboard files and model architecture file for visualisation. I have also made an api using fastAPI for it and tested it using postman. Finally I did some stress testing using locusts and have given the html file containing the locusts benchmarking data as well.

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BiLSTM model to predict an internal state when given the external state. Also making it into an API and doing stress tests.

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deep-learning locust bilstm fastapi

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