Dear Sir/Madame,

I am Dzekem Christa a Computer Engineering graduate with passion in bringing out insights from data there by improving a healthy growth. This interest has made me learn a lot within a short period of time due to my high curiosity to new discovery, flexibility and adaptability. I have a number of Data science projects I have worked on which in the process I am now able to implement some of the vital skills in this domain like:

Data cleaning, Exploratory Data Analysis, Inferential Statistics, Supervised Machine learning models, Unsupervised Machine learning models, Evaluation of model performance using model evaluation metrics, Model generalization (this resolves underfitting or overfitting) and Hyper parameter tuning for better model performance

Implementing all these measures when building a machine learning system greatly improves model performance and thus making the model produce consistent results to unseen data.

Findings from the chosen model must therefore be brought out in the form of a story. This is also very important as it is a way of transforming the tech language into a business understandable language. I have certifications on data visualization and Innovative story telling where persuasive stories are told from data.

I therefore belief I will add more value and motivation to other team members as my zeal and passion for bringing out insights from data and also making predictions with this data is high.

On my github account are some of the projects I have worked on:

Thanks for your consideration and hope to hear from you soon.

Regards, Dzekem.

Personal information
Full name: Dzekem Christa
User name: dzekem
First 500 volunteers
Volunteer background
Education: Bachelor's on Computer Engineering (University of Buea)
LinkedIn profile
Github profile
Volunteer availability
Start date: None
End date: None
Hours available per week: 15
Volunteering interests
No stated preferences.
Computer Science (Algorithms)
Social Science (Economics, Sociology, etc.)
Data Visualization
Experience working on real-world problems using data
Data Analysis
Decision Trees
Random Forests
Unsupervised models
Semi-Supervised models
Time Series Models
Neural Networks / Deep Learning

Volunteer projects

Project name Organization name Social impact area Project summary Task name Task status
Social Media for Public Health The George Washington University School of Engineering and Applied Science Education We are conducting several studies using social media to better understand public health trends and misinformation around COVID-19. Project scoping Started
GraphLab and IDDP Mapping the Spread The George Washington University School of Engineering and Applied Science Education Dr. Howie Huang’s GraphLab, together with Dr. David Broniatowski and IDDP (Institute for Data, Democracy, and Politics) researchers, is working to map the prevalence and spread of attitudes towards COVID-19 on online social media platforms. They are examining repositories of social media data related to the epidemic, starting as early as January 2020, to map the spread of discussion, information, and attitudes towards the disease and the public health response to the outbreak. Project scoping Pending review