FCSAmerica Lead Generation

This project utilizes machine learning and data science techniques to build predictive models to generate leads for the Farm Credit Services sales team. Using publicly available data sets, we have developed models in the Python and R programming languages that can successfully predict high-value customers. These customers can then be mapped back to the company\u27s internal database and lead management software for utilization in the company\u27s operations. Through this work, we have proven the ability to apply machine learning and data modeling to the agriculture industry and extract useful and actionable insights from publicly available data

FCSAmerica Lead Generation

This project utilizes machine learning and data science techniques to build predictive models to generate leads for the Farm Credit Services sales team. Using publicly available data sets, we have developed models in the Python and R programming languages that can successfully predict high-value customers. These customers can then be mapped back to the company\u27s internal database and lead management software for utilization in the company\u27s operations. Through this work, we have proven the ability to apply machine learning and data modeling to the agriculture industry and extract useful and actionable insights from publicly available data

FCSAmerica Lead Generation

This project utilizes machine learning and data science techniques to build predictive models to generate leads for the Farm Credit Services sales team. Using publically available data sets, we have developed models in the Python and R programming languages that can successfully predict high-value customers. These customers can then be mapped back to the company\u27s internal database and lead management software for utilization in the company\u27s operations. Through this work, we have proven the ability to apply machine learning and data modeling to the agriculture industry and extract useful and actionable insights from publically available data

FCSAmerica Lead Generation

This project has involved using data science and machine learning to help prioritize leads for FCSAmerica. Lead prioritization is done via a ranked list created from a model based on real, publicly available data. The model development process involved numerous steps including data cleaning, feature creation, model building, and validation. Various tools were used during this project including R, Python, and SQL. The ranked list outcome of this project, along with the modeling documentation, will be very beneficial for FCSAmerica. It will improve their sales and give them a head start on their own internal data science projects

FCSAmerica Lead Generation

This project has involved using data science and machine learning to help prioritize leads for FCSAmerica. Lead prioritization is done via a ranked list created from a model based on real, publicly available data. The model development process involved numerous steps including data cleaning, feature creation, model building, and validation. Various tools were used during this project including R, Python, and SQL. The ranked list outcome of this project, along with the modeling documentation, will be very beneficial for FCSAmerica. It will improve their sales and give them a head start on their own internal data science projects