Outlier Detection — Theory, Visualizations, and Code

Dimitris Effrosynidis

Dimitris Effrosynidis

Medium

Experienced Data Scientist with a Ph.D. in Data Science, blending 6+ years of research expertise with 4+ years in business. Proven track record in analytics, programming, and modeling. Published 14 papers, executed successful projects, and showcased skills through blogging and GitHub. Dedicated to ongoing learning and staying abreast of industry trends.

Hard Skills

Data Mining
Data Analysis
Data Mining
Generative AI
Data Visualization
Machine Learning
Feature Engineering
Time Series Forecasting
Anomaly/Outlier Detection
Natural Language Processing
Supervised/Unsupervised ML

Tools

Python
Pandas, Numpy, SciPy
Scikit-Learn
SkTime
LightGBM, XGBoost
PyOD, Shap
Matplotlib, Seaborn
Plotly, Dash
Jupyter, Anaconda
Docker, Git
Django, React
MLflow, Airflow, AWS
MySQL, PostgreSQL
MongoDB
LaTeX, Overleaf
Notion, Jira, Confluence

Outlier Detection — Theory, Visualizations, and Code

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Check this article which is available on Towards Data Science here!

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