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Led crop density estimation project, achieving 95% accuracy from drone images using object segmentation models.

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Developed crop yield prediction model, saving €1,259/month.

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Created farm reporting tool, reducing reporting time by 20 hours AWS and google docs APIs.

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Optimized shipping, increasing net profit by 20% and cutting carbon footprint by 90%

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Translate statistical formulas and models into working system code.

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Use of Tensorflow in developing Deep learning models for Computer Vision improving on the

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previous methods in terms of higher classification accuracy and performance when interfaced with

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software and adding value to the final software product.

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Computer vision projects in Object detection, classification and recognition and optical character

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recognition using python3.6, TensorFlow and statsmodels.

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Develop python libraries to handle predictions and classification models for easier collaboration with

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software engineers when interfacing the deep learning models.

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Use R for Time Series analysis and forecasting of high frequency data and displaying predictions on

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RShiny dashboard adding value to clients using predictions for better decision making.

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Working in Software Engineering capacity to develop final product installers where Docker was used

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to deploy the systems on debian and windows platforms.

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PostgreSQL to store large volumes of data and create an API with django rest framework for query

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by other team members, use of SQL to clean data of duplicates finding rows with missing fields and

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invalid data which reduced its volume and enhanced its value during transformation.

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Research and development in detecting and recognition of highly occluded objects in real life

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environments.