Talking about Games
Game Theory 101: terms and concepts- 23232Murphy2025-03-23
There's a right way to be wrong
How to incorporate business context into your predictions via cost of false positives & negatives- 21199Murphy2025-03-23
Do European M&Ms Actually Taste Better than American M&Ms?
An overly-enthusiastic application of science and data visualization to a question we’ve all been asking- 28023Murphy2025-03-23
The Next AI Revolution: A Tutorial Using VAEs to Generate High-Quality Synthetic Data
Leverage the BasicVAE architecture to generate synthetic data and improves the classification accuracy on an imbalanced dataset- 27850Murphy2025-03-23
Introducing NumPy, Part 4: Doing Math with Arrays
Plus reading and writing array data!- 25680Murphy2025-03-23
PySpark Explained: The InferSchema Problem
Think before using this common option when reading large CSV's- 22189Murphy2025-03-23
Nine Rules for SIMD Acceleration of Your Rust Code (Part 1)
General Lessons from Boosting Data Ingestion in the range-set-blaze Crate by 7x- 21384Murphy2025-03-23
ASCVIT V1: Automatic Statistical Calculation, Visualization and Interpretation Tool
Automated data analysis made easy: The first version of ASCVIT the tool for statistical calculation, visualization and interpretation- 29258Murphy2025-03-23
Football and Geometry – Passing Networks
Analyzing Bayer Leverkusen's Passing Networks from Last Season- 20507Murphy2025-03-23
What Makes a Great Data Business
Including an easy-to-use data business evaluation cheat sheet- 23381Murphy2025-03-23
The Dangers of Deceptive Data–Confusing Charts and Misleading Headlines
A deep dive into the ways data can be used to misinform the masses- 20794Murphy2025-03-23
The Data Strategy Choice Cascade
What your data strategy should look like- 22379Murphy2025-03-23
Model Management with MLflow, Azure, and Docker
A guide to tracking experiments and managing models- 25730Murphy2025-03-23
How LLMs Work: Reinforcement Learning, RLHF, DeepSeek R1, OpenAI o1, AlphaGo
Part 2 of the LLM deep dive- 23801Murphy2025-03-23
Efficient Model Fine-Tuning with Bottleneck Adapter
How to fine-tune Transformer-based models with bottleneck adapters- 22899Murphy2025-03-22
4 Pandas One-Liners That Solve Particular Tasks Efficiently
Complex tasks completed in a quick and simple way.- 20163Murphy2025-03-22
Supercharge Training of your Deep Learning Models
Super Convergence with One-Cycle Learning Rates- 26130Murphy2025-03-22
Learn to Unlearn Machines
A data-driven approach to machine unlearning of generative language models- 27147Murphy2025-03-22
Build a Convolutional Neural Network from Scratch using Numpy
Master Computer Vision by building a CNN from scratch all by yourself.- 20302Murphy2025-03-22
Defining Artificial General Intelligence
How do you know when a system has reached AGI?- 23499Murphy2025-03-22
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.