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Traditional Approach\n![trend_forecast](images/trend_forecast.png)\n\n![forecast](images/forecast.png)\n\n## Neural Networks Approach\n![nn_train_forecast](images/nn_train_forecast.png)\n\n![nn_test_forecast](images/nn_test_forecast.png)\n\n## Dataset\n- https://www.kaggle.com/datasets/varpit94/apple-stock-data-updated-till-22jun2021/data\n- this is apple stock dataset\n- currency is in USD\n- available at daily level\n- updated till 2021\n\n## Approach\n- [Neural Networks](Timeseries_Model.ipynb)\n- [Traditional Machine Learning](Apple_Forecast.ipynb)\n\n## Criteria\n- free dataset with the minimum of 1000 sample\n- must use LSTM\n- validation set 20% from total dataset\n- use model Sequential\n- must use learning_rate on optimizer\n- MAE \u003c 10% of the data scale\n### Optional Criteria (5*)\n- dataset minimum 10000 sample\n\n\u003e note: this project has been executed, you only need to 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