The following are projects done by our team – many clients wanted to be anonymous in our reference, hence we will only describe projects.
Machine Learning (ML) in Healthcare.
Identifying Diseases and Diagnosis
Machine Learning applications in healthcare is the identification and diagnosis of diseases and ailments which are otherwise considered hard-to-diagnose. This can include anything from cancers which are tough to catch during the initial stages, to other genetic diseases.
Medical Imaging Diagnosis
Machine Learning and Deep Learning are both responsible for the breakthrough technology called Computer Vision. This has found acceptance in the InnerEye initiative developed by Microsoft which works on image diagnostic tools for image analysis.
Machine Learning and AI in the Renewable Energy Sector.
Improved asset management and its maintenance, efficient operations management, workflow and portfolio management.
Smart grids, improving operations management and ensuring efficient usage and storage of renewable resources.
Prediction of a Dam’s Hazard Level - A Case Study from South Africa.
Does prediction of their multiple hazard levels. In addition, South Africa lacks skilled personnel’s to classify these dam’s hazards.
Under such a framework, this work is an application of single and collaborative decision trees in a multi class supervised learning framework to predict the hazard level of a dam.
The result obtained is highly promising, at above 94% accuracy. With the implementation of the algorithm, we expect to address the problem of scarcity of skilled individuals.
Machine Learning in Python for Weather Forecast.
The availability of meteorological data from multiple online sources is an advantage. In order to simplify the retrieval of data, a Python API to read meteorological data has been developed, and Artificial Neural Network models have been developed using TensorFlow.
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AI & Jobs
Machine Learning (ML) in Healthcare
Machine Learning and AI in the Renewable Energy Sector
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