Archives

Exploring how physics and biology intertwine, inspired by the 2024 Nobel Prize in Physics.

Exploring the 5 key challenges of applying AI to the life sciences.

Behind Johns Hopkins' breakthrough surgical bot lies a brilliantly literal naming convention. Let's dissect why SRT-H isn't just random alphabet soup.

Johns Hopkins and Stanford just pulled off something remarkable: an AI-guided surgical robot that autonomously extracted bile ducts. Here's why this changes everything.

How we used Random Forest and permutation importance to increase business value in churn prediction

Development of a machine learning model to detect phishing websites using supervised classification techniques.

How Chile’s socialist government tried to reinvent economic planning using cybernetics—and why its legacy still matters.

AI-generated images flood our feeds, but they’re built on uncredited, uncompensated creative labor. Are artists being erased?

A post about the metaphorical and literal senses of distance.

A simple Python project for managing prioritized tasks.

A personal reflection on finishing Beazley’s advanced Python course — and how it changed the way I code and reason.

Bringing together coroutines, async logic, exceptions, and object-oriented design to solve a final puzzle from Beazley’s course.

From coroutines to communication — implementing a protocol for asynchronous message handling using asyncio.

How to compose coroutines using yield from and return values from generator pipelines.

How generators and coroutines enable lightweight, cooperative concurrency by yielding control in Python.

A closer look at how exceptions propagate through the call stack and how to read and use Python’s stack traces effectively.

How to craft your own exceptions and manage failure gracefully using Python's exception system.

Understanding how context managers work under the hood — and how to build your own using __enter__ and __exit__.

Reinventing the stack data structure in Python to understand object-oriented design and control flow.

A hands-on introduction to coroutines in Python using send(), yield, and the power of interactive pipelines.

Learn how to refactor procedural code into a clean, lazy-processing pipeline using Python generators.

From raw CSV files to structured reports — building a simple financial data pipeline using Python, inspired by David Beazley’s course.

Reflections on taking an advanced Python course with David Beazley — and how it reshaped my understanding of the language.

From understanding the CSV format to converting, reading, and downloading files using Python. A complete beginner-friendly guide.