Anye DEN WARREN is an Innnovative thinker with interest in applying technology to improve efficiency in public instituitions especially in Africa
.I am open to collaboration in building systems that target public instituitions,NGOS and public-private partnership across Africa
Data Science, Machine Learning and Signal Processing
linkedin: @anyeigwacho
Medium: Blog on African Public Policy
ResearchGate: Articles and Projects.
Founder of Reastech: Reastech
In this project we implemented multiple Machine learning models to classify MRI images under Healthy, Mild cognitive impairment and dementia, we obtained 86.7% accuracy for SVM,86.7% for Naïve Bayes, 75% for KNN and 86.7% for Random Forest
In this project we looked at the effect of GDP growth on population growth of 24 African countries divided among 3 subregions namely East Africa,West Africa and Southern Africa
In this project,we implemented the famous Pan-Tompkins algorithm on multiple Electrocardiogram(ECG) signals(ECG 4, ECG 5, ECG 6), In other to determine the Total Number of heartbeats, Beats per mins, Average RR Interval, Standard Deviation of RR Interval, Average QRS width.
In this project we investigated the impact of foreign direct investment(FDI) on macroeconomic development factors(National income and GDP per capita) in V4 countries(Czech Republic,Hungary,Poland and Slovakia).
In this project we used the weight and cholesterol levels of 370 individuals as training set to learn to predict their systolic blood pressure level.
In this report we implemented the following machine learning algorithm on biomedical data sets: feed-forward neural network using backpropagation on the fisher iris data set, regularized linear regression and bias variance and SVM in determining the normal, elevated and stage1 high blood pressure of a patient give the systolic and diastolic blood pressures.
In this project we implemented the following filtering and processing techniques:Negative transformation, Log transformation, Power-law transformation, Contrast stretching, Dynamic Range expansion, Intensity level slicing (gray level slicing), Bit plane splicing and filtering with Edge kernel .