Implementation of Facebook Prophet Forecasting model to an existing web application

We have a web application that helps customers conduct forecast their product usage or service provision using time serious data. Customers upload their historical consumption or service data to the application, the application passes the customers historical data to the Facebook Prophet model, a procedure developed bu Facebook for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects, and received forecasted amounts from the model back.

The project will have one milestone and is to efficiently implement fbprophet model in a separate server and develop efficient API communication between our web app and the model. The freelancer is required to install fbprophet in their own test server and implement the API communication between the two applications. Once we test for the performance of the forecasting process and API communication between the two applications, a freelancer will be required to implement the solution on our own server. We will then release the milestone.

Remember, the key task here is to make the forecasting process for our customers efficient in terms of speed and accuracy.

We need this by the end of the day tomorrow August 4. The deadline is strict and there is no compromise on that.



Skills: Machine Learning (ML), Financial Forecasting, Python, .NET

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( 5 reviews ) Pacoima, Ethiopia

Project ID: #26813163

12 freelancers are bidding on average $1659 for this job

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