- Built a machine learning system with a validation f1 score of 71% to detect lymphovascular invasion (the invasion of cancer cells in the blood vessels or the lymphatic system) using the genome data of patients. - Trained a machine learning model to detect keratinizing squamous cell carcinoma (a medical disorder when the outer squamous cells of the epidermis, or skin's outer layer, grow out of control) using the gene expression data of patients. The model had an f1 score of 76%. - Trained a machine learning model, with a validation f1 score of 91%, to classify the histologic type of cancer using the genome data of patients. - Applied predictive modelling, statistics, machine learning, and other data analysis techniques to explore, and extract insights from the structure and unstructured cancer-related data using Python, and SQL. - Conducted several experiments and built machine learning and deep learning model to predict the survival rate of cancer patients using their gene expression matrix data. - Wrangled and feature-engineered complex medical data to improve its quality. Perform exploratory data analysis to extract insights from data. - Deployed models locally and managed the machine learning project lifecycle using Mlflow.

University of Uyo | Jun 2021 - Apr 2022

Machine Learning Facilitator

- Designed an AI lab manual and taught masters & PhD students in the Computer Engineering department how to implement some machine learning algorithms in python using scikit-learn and keras. - Collaborated with masters & PhD students in conducting research related to AI in cybersecurity, healthcare, telecommunication and education industries.

Freelance | Jan 2021 - Present

Data Scientist

● I perform data cleaning & data verification to improve the data quality and make sure it is ready for analysis. I also write reports on the data cleaning process. ● Responsible for analyzing clients’ monthly expenditures to help them create future budgets to manage cash flow more efficiently. ● I train machine learning models to perform regression analysis, classification and clustering. Integrate model to Flask REST Application Programming Interface (API). Deployment of models to Heroku.

Section | Dec 2020 - May 2022

Guest Contributor

I wrote articles that break down complicated concepts in Data Science & Machine Learning into simple edible pieces—that beginners can understand. https://www.section.io/engineering-education/authors/iniabasi-affiah/

CodeSource.io | Oct 2020 - Feb 2021

Technical Writer

I wrote articles that break down complicated concepts in Data Science & Software Engineering into simple edible pieces—that beginners can understand. https://codesource.io/author/iniabasi/

KodeHauz | Jul 2020 - Dec 2020

Electronics Trainer

I trained new interns on basic Electronics, organized hands-on practicals to reinforce their learning.

KodeHauz | Jul 2019 - Dec 2019

Machine Learning and Embedded Systems Intern

- Helped the company with data collection & data preprocessing for Machine Learning projects. - Performed Quality Assurance Testing on their software products and suggested features for their software. - Learned the basics of machine learning with Andrew Ng's Machine Learning course on Coursera. - Learned how to use Multisim and Proteus for simulation. I learned Arduino basics.

My Education

Take a look at my formal education

Nanodegree, ALX-T Data AnalystUdacity | 2022

Bachelor of Engineering - BE, Computer EngineeringUniversity of Uyo | 2020

About Me

I am passionate about leveraging the power of artificial intelligence and data to solve healthcare and business problems. I love getting my hands dirty with data and figuring out trends and patterns in them.

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