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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, 20263 min read

Creating Interactive Drop-Down Menus for Data Filtering in Dash

Add a Dash dropdown menu using the unique values from the 'manufacturer' column to enable future filtering of the graph. Watch this...

April 19, 20264 min read

Navigating Terminal and Running a Dash App on Mac and Windows

Navigate to your project directory in the terminal, activate the dvenv environment, run app.py with the Python command, and open the...

April 19, 20263 min read

Visualizing and Predicting Classes with Scatterplot and KNN

Visualize and classify a new data point using the KNN model. Watch this tutorial to learn the key concepts and techniques.

April 19, 20264 min read

Standard Deviation and the Bell Curve

Explain standard deviation as a measure of how values spread out from the mean in a normal distribution. Watch this tutorial to learn the...

April 19, 20264 min read

Prediction Accuracy: Analyzing Model Performance

Evaluate model predictions using accuracy score and analyze errors. Watch this tutorial to learn the key concepts and techniques.

April 19, 20263 min read

Mode: Finding the Most Common Value in Data Analysis

Calculate the mode to identify the most frequently occurring value in a dataset. Watch this tutorial to learn the key concepts and...

April 19, 20262 min read

K-Nearest Neighbors with Iris Flower Data Visualization

Visualize how K-Nearest Neighbors classifies iris species using multidimensional data. Watch this tutorial to learn the key concepts and...

April 19, 20262 min read

Understanding K-Nearest Neighbors in Supervised Learning

Classify new data points by comparing them to their closest labeled neighbors. Watch this tutorial to learn the key concepts and techniques.

April 19, 20266 min read

Python Virtual Environments with Conda for Project Isolation

Learn how to create and manage Python virtual environments using Conda to keep your project dependencies isolated and organized.

April 19, 20264 min read

Creating Interactive Data Dashboards with Dash and Python

Discover how to build interactive web dashboards using Dash and Python, converting code into dynamic HTML interfaces with live data updates.

April 19, 20266 min read

Neural Network Predictions: Accuracy and Fine-Tuning

Evaluate model predictions on test images and compare them to actual labels to assess accuracy. Watch this tutorial to learn the key...

April 19, 20263 min read

Linear Regression: Predicting Relationships in Data

Explore linear regression to predict y values from given x data points by minimizing variance. Watch this tutorial to learn the key...

April 19, 20266 min read

Accessing DataFrame Rows and Columns

Use .iloc and .loc with correct indexing and slicing to select specific rows and columns from a Pandas DataFrame. Watch this tutorial to...

April 19, 20264 min read

Filling Missing Age and Embarked Data for Titanic Analysis

Fill missing age values with gender-based means and replace missing embarked entries with the mode value 'S'. Watch this tutorial to learn...

April 19, 20262 min read

Visualizing Predictions with KNN on Flower Data

Implement and visualize a simple k-nearest neighbors classifier to predict a new data point's class. Watch this tutorial to learn the key...

April 19, 20266 min read

Regression and Data Analysis with Python Libraries

Review statistical libraries, Python data science basics, and data loading with Pandas in Jupyter Notebooks. Watch this tutorial to learn...

April 19, 20263 min read

Exploring Logistic Regression for Employee Retention Prediction

Introduce logistic regression to predict employee attrition using HR data. Watch this tutorial to learn the key concepts and techniques.

April 19, 20262 min read

Continuous Classification: Linear Regression Explained

Use linear regression to predict continuous numeric values by fitting a line to data. Watch this tutorial to learn the key concepts and...

April 19, 20262 min read

Training and Testing Linear Regression Models

Train the linear regression model using X train and Y train data. Watch this tutorial to learn the key concepts and techniques.

April 19, 20262 min read

Visualizing and Interpreting Data

Check data for null values, confirm none exist, verify class imbalance, and examine random samples visually. Watch this tutorial to learn...

April 19, 20263 min read

Preparing Titanic Dataset: Splitting and Scaling Techniques

Next, we're going to split our data. We don't actually need to split it quite as much as we normally do.

April 19, 20261 min read

Unveiling Stock Data: Navigating Dictionaries to Find Key Metrics

For your first challenge today, I'd like you to take a look at this data dictionary that we got back and try to see if you can find the...

April 19, 20262 min read

Exploring the K-Nearest Neighbors Algorithm

Here in part three, we're going to be working on the k-nearest neighbors machine learning algorithm. The k-nearest neighbors algorithm is...

April 19, 20263 min read

Neural Network Training Process for Digit Recognition

Before we start normalizing data, getting it all set up, and training our model, let's talk about that process a little bit more. We're...