Gideon H.

Gideon H.

NairobiKenya

Data science and machine learning expert

PERSONAL PROFILE Successfully completed a project on creating an algorithm to determine the diabetic status of pregnant women using features such as blood pressure and number of pregnancies. I employed various classification models such as SVM, Decision tree and XGboost for the project. Used random forest regression to predict fantasy football scores. Regular contributor to Machine Learning project on GitHub. Excelled in machine learning and data science coursework. Completed a senior project to predict loan defaults by clients of a particular bank. Used decision trees, regression models, and SVM to accomplish the project. SKILLS * Am well skilled with handling a computer device with supervision or no supervision. * I am skilled in the creation of algorithmic models that can be used for data analysis aiding in provision of data-driven decisions. * I have outstanding communication skills in all official languages.

Skills

Gideon H.

Gideon H.

NairobiKenya

Data science and machine learning expert

Specializes in
PERSONAL PROFILE Successfully completed a project on creating an algorithm to determine the diabetic status of pregnant women using features such as blood pressure and number of pregnancies. I employed various classification models such as SVM, Decision tree and XGboost for the project. Used random forest regression to predict fantasy football scores. Regular contributor to Machine Learning project on GitHub. Excelled in machine learning and data science coursework. Completed a senior project to predict loan defaults by clients of a particular bank. Used decision trees, regression models, and SVM to accomplish the project. SKILLS * Am well skilled with handling a computer device with supervision or no supervision. * I am skilled in the creation of algorithmic models that can be used for data analysis aiding in provision of data-driven decisions. * I have outstanding communication skills in all official languages.

Skills

More than 30 hrs/week