Attakorah Samuel
Company: Carolina University
Position: Precision Agriculture Data Scientist
Expert Summary
Samuel Attakorah is a Precision Agriculture Data Scientist with expertise in machine learning and data analytics. They have worked on projects optimizing crop yields using models like Random Forest and LSTM, addressing climate change and sustainable farming. A participant in the "Future Crop Challenge" on Kaggle, Samuel leverages AI to support agricultural decision-making. They have also contributed to agricultural research initiatives, advancing precision agriculture through data-driven solutions.
Publications
https://scholar.google.com/citations?view_op=list_works&hl=en&hl=en&user=fO9VxXkAAAAJ
Education
Master of Science in Data Science
Experience
Forum for Agricultural Research for Development – Knowledge Management / Frontend Developer
At the Forum for Agricultural Research in Africa (FARA), Samuel Attakorah contributed significantly to agricultural research and knowledge management across the African continent. They revamped various platforms, including a gender-sensitive database for farmer registration and an e-library, enhancing user engagement and accessibility. Their work at FARA supported the coordination of agricultural research, focusing on transforming Africa into a sustainable knowledge society.
Research Assistant – Carolina University
As a Research Assistant, Samuel Attakorah utilized Python, PySpark, and Databricks to analyze Google Play Store data and trained machine learning algorithms to predict cancer types with over 92% accuracy. This experience solidified their expertise in data analytics and machine learning, laying the groundwork for their future endeavors in precision agriculture.
Post-Graduate Work – Plant Disease Detection System
After completing his studies, Samuel Attakorah worked on developing a machine learning-based plant disease detection system. Using image processing and AI models, they accurately identified plant diseases, supporting farmers in early disease detection and efficient crop management. This project further demonstrates his commitment to advancing precision agriculture through innovative technology.
