DSLP – The Data Science Project Management Framework that Transformed My Team
It is the best framework for Data Science, by far. Use it for your team or for just yourself. Here's how I used it.- 28620Murphy2025-03-23
How Can We Continually Adapt Vision-Language Models?
Exploring Continual Learning Strategies for CLIP.- 25877Murphy2025-03-23
How to Achieve Near Human-Level Performance in Chunking for RAGs
The costly yet powerful splitting technique for superior RAG retrieval- 23148Murphy2025-03-23
When AI Artists Compete:
Insights from My Generative Art Experiment- 22313Murphy2025-03-23
No Baseline? No Benchmarks? No Biggie! An Experimental Approach to Agile Chatbot Development
Lessons learned bringing LLM-based products to production- 24934Murphy2025-03-23
How to Easily Set Up a Neat User Interface for Your Local LLM
A step-by-step guide to run Llama3 locally with Open WebUI- 29394Murphy2025-03-23
PySpark Explained: Delta Table Time Travel Queries
Delete, recover, and replay historical data transactions- 22260Murphy2025-03-23
Let's Write a Composable, Easy-to-Use Caching Package in Python
Easy, user-friendly caching that tailors to all your needs- 26279Murphy2025-03-23
Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners
One (tiny) dataset, six imputation methods?- 24076Murphy2025-03-23
AWS DeepRacer : A Practical Guide to Reducing The Sim2Real Gap – Part 2 || Training Guide
This article describes how to train the AWS DeepRacer to drive safely around a track without crashing. The goal is not to train the...- 24771Murphy2025-03-23
Sequential Testing: The Secret Sauce for Low-Volume A/B Tests
How to Accelerate Decision-Making with Low Volume Data- 21064Murphy2025-03-23
The MMD-Critic Method, Explained
A powerful yet under-the-radar method for data summarization and explainable AI- 27545Murphy2025-03-23
Building a Robust Data Observability Framework to Ensure Data Quality and Integrity
How can we improve observability with open-source tools?- 26434Murphy2025-03-23
Boosting LLM Inference Speed Using Speculative Decoding
A practical guide on using cutting-edge optimization techniques to speed up inference- 22563Murphy2025-03-23
Exploring the Strategic Capabilities of LLMs in a Risk Game Setting
In a simulated Risk environment, large language models from Anthropic, OpenAI, and Meta showcase distinct strategic behaviors, with Claude...- 25609Murphy2025-03-23
Need for Speed: Streamlit vs Functool Caching
Comparing the performance of streamlit and functools caching for pandas and polars. The results will surprise you!- 29858Murphy2025-03-23
How to Color Polars DataFrame
Continue working with the Polars library while being able to color and style the table- 21916Murphy2025-03-23
Analytics Frameworks Every Data Scientist Should Know
Why I believe my experience at McKinsey made me a better data scientist- 26993Murphy2025-03-23
Machine Learning Operations (MLOps) For Beginners
End-to-end Project Implementation- 26961Murphy2025-03-23
Beating Connect Four with AI
A Simple Approach Using Monte Carlo Simulations- 24994Murphy2025-03-23
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.