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Datapreneur Administrator
Sep 29, 2021
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Datapreneur Administrator
Jul 29, 2021
In Resources
We are interested in machine learning and finance. During our journey, we began forking people. We love forking people. Feel free to fork us too! Some good forks you may be interested in: https://github.com/fintasticData/StockForecast https://github.com/fintasticData/DataScienceTools
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Datapreneur Administrator
Jul 29, 2021
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Datapreneur Administrator
Jul 26, 2021
In Resources
"Vulekamali is a project by the South African National Treasury and Imali Yethu with the goal of making government budget data and processes accessible to all citizens & interested parties." The vulekamali portal has a wealth of government financial data available. Connect and get creating!
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Datapreneur Administrator
Jul 26, 2021
In Resources
Prophet is a procedure 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. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is open source software released by Facebook’s Core Data Science team. It is available for download on CRAN and PyPI. Accurate and fast. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Fully automatic. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series. Tunable forecasts. The Prophet procedure includes many possibilities for users to tweak and adjust forecasts. You can use human-interpretable parameters to improve your forecast by adding your domain knowledge. Available in R or Python. We’ve implemented the Prophet procedure in R and Python, but they share the same underlying Stan code for fitting. Use whatever language you’re comfortable with to get forecasts. Link to Anaconda download (FOLLOW THE INSTALLATION INSTRUCTIONS for a clean installation!!!) https://anaconda.org/conda-forge/fbprophet
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