Isaac Kwabena Owusu-Appiah

Data Scientist

Data Scientist & Machine Learning enthusiast

I'm a results-driven Data & Machine Learning enthusiast, skilled in assisting corporates with the definition and implementation of their Data and Analytics use cases; from business understanding to creating the final Analytics solutions and building ML models. Experienced in the complete product development lifecycle of software applications. A fast learner focusing on end-to-end implementation of ideas. My work experience cut across data analysis, data visualization, statistical inference, descriptive statistics, data science, natural language processing, deep learning and machine learning and business administration. I have understanding of complex analytical methods, Data management, Operations research, Database Schema and data warehouse design.

Resume

My learning path

2017

Mphil Statistics: Sample Survey, Catgorical Data Analysis, Regression Analysis, Probability and probalility Distributions.

2019

2020

2021

Master's thesis on Machine learning phishing detection from URL.

2023

Associate Data Scientist in Python DataCamp course for the data professional and researcher.


My skills:

1 - Basic 2 - Novice 3 - Intermediate

4 - Advanced 5 - Expert

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Programming languages

Python - 4

>4 years experience

R - 4

4 years experience

SQL

<4 year experience
Machine learning

Supervised ML - 5

Classification & Regression, Computer Vision, Time Series

Unsupervised ML - 5

K-Means, K-Medoids, Hierarachial Clustering, PCA

Deep learning - 3

PyTorch, Tensorflow, HuggingFace, CNN
Software engineering

Front-end - 2

HTML, CSS, JavaScript

Databases - 5

SQL, MongoDB

Deployment - 2

Streamlit, Heroku
Data analysis

Data wrangling - 4

Pandas, Numpy

Data visualization - 4

Plotly, Matplotlib, Seaborn

Statistics - 5

Descriptive, Inferential, Probalility