Hi
My name is Adam Pfister. I perform paid and volunteer custom data science services for a diverse range
of partners using database management, data cleaning/organizing, exploratory and statistical analysis,
visualizations, machine learning, artificial intelligence, deep learning, and natural language
processing to answer questions, uncover patterns, improve efficiency, and increase sales / customers.
Sample partners include:
- Delaware Department of Health and Social Services (reorganization task force, Wilmington, DE)
- Camp Blue Spruce (nonprofit summer camp for kids with severe food allergies, Portland, OR)
- Home Grown Apothecary (boutique recreational cannabis dispensary, Portland, OR)
- Rita's Water Ice (small business franchise, Wilmington, DE)
- Code for America (nonprofit tech community outreach, Eugene, OR)
- Lane County Information Services (improving homelessness task force, Eugene, OR)
Sample
Two Cannabis Recommender Systems. The first uses supervised machine learning to classify cannabis
strains based on their chemical lab tests, helping a retail store to better consistently market
products to customers. The second uses natural language processing to recommend cannabis strains
based on the similarity of the input strain's text description, helping the customer to identify
best fit products, similar to a Netflix recommender system.
Cannabis Recommender Systems
Predicting UFC Fights with Machine Learning. This project uses exploratory data analysis, feature
engineering, and supervised learning models to theoretically predict the winner of a UFC fight with
79% probability using only a handful of fighter attributes.
Predicting UFC Fights with Machine
Learning
What Makes a Winning Fighter? Clustering UFC Fighter Attributes with Unsupervised Learning. In this project
I attempt to use unsupervised learning and dimensionality reduction methods to discover the patterns
and key attributes that make a winning fighter. Methods include feature engineering, discovery analysis,
Kmeans, principal component analysis (PCA), T-sne, and mean shift.
What Makes a Winning Fighter? Clustering UFC Fighter Attributes
Discovery Analysis of Mass Shootings in America. Mass shootings seem like they are in the news at increasing
rates each year. What do the numbers say?
Discovery Analysis of Mass Shootings in America
Bio
I hold two degrees, an Associate's in Business, and a Bachelor of Science in Philosophy from the
University of Oregon. Sample topics include formal logic, critical thinking, ethical decision
making, pragmatism, public speaking, artificial intelligence, economics, linguistics, computer
science, and statistics.
I have worked in banking (3 years), full-time currency trading (5 years), helped found a cannabis
dispensary (COO 3 years), consulted for the cannabis industry (2 years), and have been
consulting in data science proper since October 2019.
In 2019, I completed a 600-hour data science certification with an online company called Thinkful,
dual-specializing in natural language processing (NLP) and time-series analysis. Thinkful provides
an immersive data science course including a self-paced online curriculum, live 1-on-1 mentorship
with real world data scientists, and polished portfolio projects showcasing everything learned
throughout the course.
Sample topics learned: Python, SQL / Postgres, Numpy / Pandas, Matplotlib / Seaborn, scikit-learn,
Jupyter / Google colab, data wrangling / cleaning, visualizations, discovery analysis,
classification / regression, statistics / probability, hypothesis A/B testing, API / web scraping,
AI / machine learning, TensorFlow / Keras, deep learning, natural language processing (NLP)
Connect
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while (!deck.isInOrder()) {
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print 'It took ' + i + ' iterations to sort the deck.';
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