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Time-series-forecasting

Using MongoDB as database and Fastapi to achieve functions

model_repo contains 8 models include DCNN and 7 different models

api_test now include 5 api, run_process_forecast first read csv file and store it into database, then do the training and evalution from begining and store the performance into datebase as well. get_model_mape using uuid to find the model performance. get_pred_value using uuid and model no. to find the pred_value and time.check_status using uuid to check the status of the progress. get_historical_data using uuid to get the historical data of the dataset.

dataprocessing.py contains some functions to process and evalate the date and model.

server is the fastapi server

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Using MongoDB as database and Fastapi to achieve functions

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