Colin Jaffe
Colin Jaffe is a programmer, writer, and teacher with a passion for creative code, customizable computing environments, and simple puns. He loves teaching code, from the fundamentals of algorithmic thinking to the business logic and user flow of application building—he particularly enjoys teaching JavaScript, Python, API design, and front-end frameworks.
Colin has taught code to a diverse group of students since learning to code himself, including young men of color at All-Star Code, elementary school kids at The Coding Space, and marginalized groups at Pursuit. He also works as an instructor for Noble Desktop, where he teaches classes in the Full-Stack Web Development Certificate and the Data Science & AI Certificate.
Colin lives in Brooklyn with his wife, two kids, and many intricate board games.
Learning Resources by Colin Jaffe
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Data Scraping: Navigating Unique Web Structures
Data scraping means adapting to what web pages actually do, not what they're supposed to do. Let's explore practical techniques to extract exactly what you need from HTML tags in Python.
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Web Scraping: Extracting Non-Truncated Titles and Prices with Python
Web scraping doesn't have to be complicated—learn how BeautifulSoup can easily extract the exact titles and prices you need. Discover simple Python tricks to turn messy HTML data into clean, usable information.
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Understanding Random Forest Classifiers: How They Work
Random forest classifiers combine multiple diverse decision trees to accurately predict outcomes. Discover how randomness creates robust models that effectively handle Titanic-sized data challenges.
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Linear Regression: Predicting Relationships in Data
Discover how linear regression unlocks the power of prediction and starts your journey into machine learning. Learn to visualize data patterns and find the best-fit line, minimizing variance for accurate insights.
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Model Accuracy: Impact of Outliers and Dataset Size
Struggling with inconsistent results from your machine learning models? Discover how handling outliers and addressing limited data size can dramatically influence your model's accuracy and reliability.
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