This portfolio is a compilation of all the AI/ML data science projects I have done for academic and self-learning purposes. Note that it also contains achievements, skills, and certificates. Finally, please feel free to check back often as it is updated on the regular basis.
- Email: [email protected]
- LinkedIn: linkedin.com/in/jonathanpoeder
- Website: japoeder.github.io
Origination Model (Credit Risk)
This project applies various classification models such as Logistic Regression (pytorch & sklearn), Random Forest, and XGBoost to solve an important origination problem in the credit risk space. The models for the most part have comparable accuracy metrics aside from xgboost, which may perform better with some additional fine tuning.
Basket Analysis (Retail Analytics)
This Instacart basket analysis is focused on understanding customer purchasing patterns using a dataset containing 3 million grocery orders from over 200,000 Instacart users. The files encompasse a variety of data on order details, product information, and the order in which products were added to the cart.
It's really easy for AWS costs to slip under the radar and accrue to unexpected amounts. While Amazon does provide some functionality with their cost explorer meant to address that, it is not as flexible in how the data can be aggregated and it isn't integrated with Slack as far as I'm aware. This project addresses that.
- Luhn's Algorithm
- The Dining Philosopher
- Cryptography: Hill Cipher
- Cryptography: Shift Cipher
- LFSR Image Encryption
- MaxFlow Playoff Problem
- n-Body Simulation
- Pascal's Triangle
- Quantum Computing
- Card Services Attrition Study
- Bank Customer Churn
- Image Classification w/ CNNs
- Twitter Airline Sentiment Analysis
- Methodologies: Machine Learning, Deep Learning, Time Series Analysis, Natural Language Processing, Statistics, Explainable AI, A/B Testing and Experimentation Design, Big Data Analytics
- Languages: Python (pandas, numpy, scikit-Learn, scipy, keras, matplotlib), SAS, SQL
- Tools: MySQL, Tableau, Git, PySpark, Amazon Web Services (AWS), Flask, MS Excel
- MLOps Concepts By datacamp
- Introduction to Deep Learning with PyTorch By datacamp
- Introduction to Natural Language Processing By datacamp
- ML with scikit-learn By datacamp
- Python Data Science Toolbox II By datacamp
- Python Data Science Toolbox I By datacamp
- Intermediate Python By datacamp
- Introduction to Python By datacamp