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Colin Jaffe

91 articles

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.

Articles

April 19, 20261 min read

Diving Deeper into Data Visualization with Dash

That concludes our course. I hope you got a lot out of it. We certainly covered a lot of ground.

April 19, 20264 min read

Precision and Recall: Improving Predictive Model Accuracy

Evaluate model performance highlighting precision, recall, and the impact of prediction errors. Watch this tutorial to learn the key...

April 19, 20263 min read

Label Encoding, Scaling, and Model Compatibility

Preprocess the test dataset by selecting columns, label encoding categorical features, and scaling numerical features. Watch this tutorial...

April 19, 20263 min read

Data for Readability: Enhancing Index and Column Clarity

Rename columns and rearrange data to improve readability and identify salary as a factor influencing employee retention. Watch this...

April 19, 20263 min read

Logistic Regression with Data Scaling and Preparation

Prepare data, split into training/testing sets, scale features, and train logistic regression model. Watch this tutorial to learn the key...

April 19, 20262 min read

Utilizing Pandas for Data Calculations and Predictions

Use pandas to create a data frame and perform vector operations to calculate predictions from attendance and concessions data. Watch this...

April 19, 20263 min read

Passenger Survival Rates: Insights from the Titanic Data

Analyze Titanic passenger survival rates by passenger class using Seaborn count plots. Watch this tutorial to learn the key concepts and...

April 19, 20263 min read

Understanding Random Forest Classifiers: How They Work

Explain how random forest classifiers average multiple diverse decision trees for robust prediction. Watch this tutorial to learn the key...

April 19, 20264 min read

Tuples: Immutable Collections in Machine Learning

Use tuple unpacking in Python to extract multiple values from immutable tuples efficiently. Watch this tutorial to learn the key concepts...

April 19, 20263 min read

Navigating and Extracting Specific Data from an API Response

Navigate the nested Python dictionary to access stock closing data for a specific date. Watch this tutorial to learn the key concepts and...

April 19, 20263 min read

Analyzing Titanic Data: Combining Class and Gender for Insights

Combine passenger class and gender into a categorical feature to analyze Titanic survival rates. Watch this tutorial to learn the key...

April 19, 20262 min read

Splitting Data into Training and Testing Sets for Modeling

Split the iris dataset into training and testing sets for features and targets. Watch this tutorial to learn the key concepts and...

April 19, 20262 min read

Exploring KNN with the Iris Dataset in Python

Apply the K-Nearest Neighbors algorithm to classify iris flowers using the sklearn iris dataset. Watch this tutorial to learn the key...

April 19, 20263 min read

Accuracy Scores in Linear Regression Models

Evaluate model accuracy using the score method, comparing predictions to the mean baseline. Watch this tutorial to learn the key concepts...

April 19, 20262 min read

Neural Network Data: Patterns in Machine Learning

Visualize numeric pixel data as an image to recognize digit patterns. Watch this tutorial to learn the key concepts and techniques.

April 19, 20262 min read

Refining Data: Removing Outliers for Improved Model Training

Remove outliers from car sales data and retrain the model. Watch this tutorial to learn the key concepts and techniques.

April 19, 20262 min read

Understanding Dataset Structure in Machine Learning

Unpack digit data into training and testing datasets and verify array shapes and types. Watch this tutorial to learn the key concepts and...

April 19, 20262 min read

Extracting Pagination Data: Navigating Web Elements

Extract the maximum page number from the pagination element using BeautifulSoup. Watch this tutorial to learn the key concepts and...

April 19, 20263 min read

Utilizing Lambda Functions in Data Science

So a lot of the functions you write when you're doing data science are these very simple functions that define an operation for you that is...

April 19, 20262 min read

The Impact of Salary on Retention Through Crosstab Analysis

Perform crosstabulation analysis to examine the relationship between salary and employee retention. Watch this tutorial to learn the key...

April 19, 20267 min read

Web Scraping: Extracting Non-Truncated Titles and Prices with Python

Scrape book titles and prices from a webpage using requests and BeautifulSoup. Watch this tutorial to learn the key concepts and techniques.

April 19, 20262 min read

Analyzing Apple Price Peaks Using Pandas for Data Insights

Find the highest apple price and corresponding date using pandas, and then plot the data. Watch this tutorial to learn the key concepts and...

April 19, 20263 min read

Handwritten Digit Recognition with Neural Networks

Explain how handwritten digit images are represented as arrays for training machine learning models. Watch this tutorial to learn the key...

April 19, 20262 min read

Versicolor and Virginica Misclassification in KNN Models

Analyze how the KNN algorithm misclassified one virginica sample as versicolor due to its proximity to versicolor data points. Watch this...