Passing Functions to Test Files in Python Pytest
This is a very frequent question, but the solution is very simple: use a fixture.- 23549Murphy2025-03-22
Dask DataFrame is Fast Now
Introduction Dask DataFrame scales out pandas DataFrames to operate at the 100GB-100TB scale. Historically, Dask was pretty slow compared to other tools in this space (like Spark). Due to a number of improvements focused on performance, it’s now pre- 23370Murphy2025-03-22
Mastering Statistical Tests (Part II): Your Guide to Choosing the Right Test for Your Data
Your guide to choosing the right test for your data- 20204Murphy2025-03-22
Intuitive Temporal DataFrame Filtration
Get rid of your ineffective code for filtering time series data- 20497Murphy2025-03-22
Introduction to Domain Adaptation- Motivation, Options, Tradeoffs
Stepping out of the "comfort zone" - part 1/3 of a deep-dive into domain adaptation approaches for LLMs- 21145Murphy2025-03-22
Physics-Informed Neural Network with Forcing Function
Solving differential equations directly with neural networks (with code)- 26656Murphy2025-03-22
Scaling Monosemanticity: Anthropic's One Step Towards Interpretable & Manipulable LLMs
From prompt engineering to activation engineering for more controllable and safer LLMs- 21449Murphy2025-03-22
An Introduction to Reinforcement Learning
A deep dive into the rudiments of reinforcement learning, including model-based and model-free methods- 29466Murphy2025-03-22
Do You Need a Degree to Be a Data Scientist?
No, but it certainly helps.- 24341Murphy2025-03-22
How I Assess the Memory Consumption of My Python Code
Different approaches to measure the memory consumption of a variable or a function- 28304Murphy2025-03-22
PyTorch Introduction – Training a Computer Vision Algorithm
In this post of the PyTorch Introduction, we'll learn how to train a computer vision model using a Convolutional Neural Network with...- 23334Murphy2025-03-22
Understanding the Two Faces of Shiny for Python: Core and Express
Exploring the Differences and Use Cases of Shiny Core and Shiny Express for Python- 29963Murphy2025-03-22
From Prompt Engineering to Agent Engineering
Introducing a Practical Agent Engineering Framework- 21837Murphy2025-03-22
Computing Minimum Sample Size for A/B Tests in Statsmodels: How and Why
A deep-dive into how and why Statsmodels uses numerical optimization instead of closed-form formulas- 26599Murphy2025-03-22
Fine-Tune Smaller Transformer Models: Text Classification
Using Microsoft's Phi-3 to generate synthetic data- 22696Murphy2025-03-22
Terraforming Dataform
Dataform 101, Part 2: Provisioning with Least Privilege Access Control- 29461Murphy2025-03-22
Policy Gradient Methods in Reinforcement Learning
Teaching a Car to Cross a Mountain using Policy Gradient Methods in Python: A Mathematical Deep Dive into Reinforcement Learning- 23160Murphy2025-03-22
Training Naive Bayes… Really Fast
Performance tuning in Julia- 26755Murphy2025-03-22
Simple Ways to Speed Up Your PyTorch Model Training
If all machine learning engineers want one thing, it's faster model training - maybe after good test metrics- 29088Murphy2025-03-22
SQL Explained: Normal Forms
Applying 1st, 2nd and 3rd normal forms to a database- 27520Murphy2025-03-22
The current state of continual learning in AI
Why is ChatGPT only trained up until 2021?
Optimizing Pandas Code: The Impact of Operation Sequence
Learn how to rearrange your code to achieve significant speed improvements.