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For current example I took currency pair UAH/USD for date range 2012-2017. \nData was getting from https://www.investing.com/currencies/usd-uah-historical-data\nThe forecast looks quite realistic, the forecast components give some ideas about seasonality. \nThe time series forecast can be used as a feature for another machine learning models.\n\n[Prophet](https://facebookincubator.github.io/prophet/) works pretty well from the box. \nYou can easily build a model for forecasting time series.\nAlso [Prophet](https://facebookincubator.github.io/prophet/docs/quick_start.html) several the hyperparameters, \nthat can help you improve your model.\n\nThere are build in tools for visualization of the prediction. You can visulaizate the forecast and the forecast components.\nThe visualization of the forecast components can help make interesting conclusions about seasonality.\n\n![the forecast components](images/yearly_seasonality.png)\n\n## Dependencies\n* Python 3.5\n* [Prophet](https://facebookincubator.github.io/prophet/)\n* [scikit-learn](http://scikit-learn.org/stable/)\n* [plotly](https://plot.ly/python/offline/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flevabd%2Fprophet-finance-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flevabd%2Fprophet-finance-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flevabd%2Fprophet-finance-prediction/lists"}