David Sasu is a Computer Scientist, Natural Language Processing Researcher and Writer.
Learn to deeply understand.
Use understood knowledge to solve important problems to help people and do the greatest good.
Teach other people how to do the same.
David is currently a PhD student in the Computer Science Department at the IT University of Copenhagen advised by Dr. Natalie Schluter. His research interest covers the field of Natural Language Processing.
In this field of Computer Science, he has particular interest in developing Natural Language Processing Systems that can function optimally on limited and small amounts of linguistic data.
David graduated with a Bachelor of Science in Computer Science from Ashesi University.
Research focuses on Natural Language ProcessingIT University of Copenhagen
Summa Cum LaudeAshesi University
Assisted in teaching the following classes: Algorithm Design, Operating Systems, Computer Organisation and Architecture and Pre-Calculus.Ashesi University
Built a speech generation software which uses the morphological and syntactic rules of the Russian language to generate various Russian word forms. This software was used to help people with speech disabilities to communicate more effectively.PRC - Saltillo
Built a desktop application with Python to generate and organize student examination schedules.University of Ghana Computing Systems
In this tutorial, we build a spam email detection program based on Machine Learning (ML). We use the Naïve Bayes Classification Algorithm in this program.
R is a free programming language and software environment which is used for statistical computing and graphics. RStudio is a free and open-source integrated development environment for R.
Many machine learning algorithms require predicting the class of given data. You can make simple predictions with the Random Forest Algorithm. It is one of the most popular machine learning algorithms used for such a task. The Random Forest Algorithm is able to predict the class of a given observation through the implementation and use of a ‘Random Forest’. ‘Random Forest’ is a term to describe several ‘decision trees’ that are working together to produce a collective output.