If you can't explain it simply, you don't understand it well enough. Albert Einstein
Natural Language Processing (NLP) is a subset of data science that applies statistical and mathematical methods to analyse, synthesise, and quantify qualitative and open-ended data such as natural languages. Applications of NLP include speech recognition ...
Big data is defined and characterised by three v's; Volume, Variety,Veracity
Deep learning is parallelized machine learning that is often implemented in specialized computing environments/clusters - possibly involving graphical processing unit (GPU) cores - in order to learn high-level features in a dataset.
Optimization concerns finding the optimal solution among competing alternatives. Mathematical optimization addresses finding the minimum/maximum of a function/task most efficiently ... out of all the possible solutions/scenarios
miRNAVISA is a web-based tool that allows customized interrogation and comparisons of miRNA families for hypotheses generation, and comparison of the per-species chromosomal distribution of miRNA genes in different families.
We have developed a web application for health informatics in Kenya. Data from the District Health Information Systems(DHIS) can complement ocassional demographic survey data thus ensuring continuous evaluation of the data accuracy, reduction of missingness, etc.
Traffic data from our roads can be used to analyse flow/flux, speed, accidents, road-use/misuse, and even tax compliance. Data-driven decisions help in policy formulation to enhance efficiency and mitigate deaths
Dragon microrna discovery (DMD) software for de-novo discovery of miRNAs from abitrary DNA/RNA sequences with high specificity and sensitivity. DMD is dedicated to the late VB!
This course gives an introduction to the core skills regarding data analysis, mathematical and statistical models and the application of algorithms to make sense from data via analysis.
A time series is a set of data points indexed by time. Time series data is ubiqutous in many industries and sectors of the economy such as banking/finance, agriculture, mining, etc.
Computational Methods and Data Analytics III has an approach based on data concerning algorithms, fractals, probability, statistics, image processing, medicine (neurology, radiology and psychiatry), and economy. Combining theory and application for each field and different datasets.
The science and art of extracting meaning from seemingly incomprehensible data is the core of this course. Students develop confidence and skills to apply statistical principles to solve practical problems in industry and public service.
