1234-Ariel-code

african-masters-of-machine-intelligence-ammi

My projects

akemogne.github.io

My website

ammi_my-final-project

In this repository, I will be working on my final project at AMMI (African Masters of Machine Intelligence) titled "Using Machine Learning to detect and predict changes of land use from aerial imagery", where we will develop a Bayesian Recurrent Neural Network approach. The aim of this project is to investigate the use of deep learning to estimate the probability of changes in urban and rural aerial imagery. To achieve that, we will need to develop novel deep learning techniques to model the temporal aspects of diverse data sources accurately. So, the all idea of this project is to predict a map of likely future changes of a city using existing maps, simulation engines, as well as overhead imagery.

applied-machine-learning-in-python

Coursera courses by University of Michigan

hamoye-data-science-internship

introduction-to-data-science-in-python

Coursera courses by University of Michigan

introduction-to-deep-learning

Coursera courses by Higher School of Economics (National Research University)

machine-learning

Coursera courses by Stanford University

mathematics-for-machine-learning-linear-algebra

Coursera courses by Imperial College London

review-papers

Here I am looking at some papers in ML particular in Computer vision related to medicine. So, most of the papers that I reproduce here are on ML applications in medicine. In other words, I will be using ML to solve some medical tasks.

1234-Ariel-code/review-papers

Here I am looking at some papers in ML particular in Computer vision related to medicine. So, most of the papers that I reproduce here are on ML applications in medicine. In other words, I will be using ML to solve some medical tasks.

1234-Ariel-code/african-masters-of-machine-intelligence-ammi

My projects

1234-Ariel-code/akemogne.github.io

My website

1234-Ariel-code/ammi_my-final-project

In this repository, I will be working on my final project at AMMI (African Masters of Machine Intelligence) titled "Using Machine Learning to detect and predict changes of land use from aerial imagery", where we will develop a Bayesian Recurrent Neural Network approach. The aim of this project is to investigate the use of deep learning to estimate the probability of changes in urban and rural aerial imagery. To achieve that, we will need to develop novel deep learning techniques to model the temporal aspects of diverse data sources accurately. So, the all idea of this project is to predict a map of likely future changes of a city using existing maps, simulation engines, as well as overhead imagery.

1234-Ariel-code/applied-machine-learning-in-python

Coursera courses by University of Michigan

1234-Ariel-code/hamoye-data-science-internship

1234-Ariel-code/introduction-to-data-science-in-python

Coursera courses by University of Michigan

1234-Ariel-code/introduction-to-deep-learning

Coursera courses by Higher School of Economics (National Research University)

1234-Ariel-code/machine-learning

Coursera courses by Stanford University

1234-Ariel-code/mathematics-for-machine-learning-linear-algebra

Coursera courses by Imperial College London

1234-Ariel-code/natural-language-processing-in-tensorflow

Coursera courses by deeplearning.ai

1234-Ariel-code/research-work

This repository contains both my master's research and PhD's research in Biostatistics