A Data Scientist skilled in Machine Learning, Python, Power BI, Web Scrapping, EDA as described on my Linkedin checkout my GitHub
and my Medium.com Posts.
In this project, I scrapped glassdoor for data scientists data using selenium, I cleaned it using python in jupyter lab, I did explanatory data analysis to get the gist of our data
I then used linear regression, lasso and random forest models for training,
I finally productionized my ML models using a python light weight flask framework.
Loan Prediction Based on Customer Behaviour
Being able to present your work in an easy-to-understand format can help sell your ideas to stakeholders and decision-makers. Streamlit give us the ability to do these things. It’s quick and painless, flexible, and native to Python
My source of data for this project is kaggle, After data cleaning using python, I used linear regression, Random forest and Vector machine models for training.
I worked on this with a team of 2 at my time with pollicy working as a software engineering fellow, since its a civic tech organisation. we worked on this project to help decision makers to use fact checkued data in decison making