Preface Welcome back to the fourth edition of my ongoing series on the basics of Linear Algebra, the foundational math behind machine learning. In my previous article, I introduced vectors, linear combinations, and vector spans. This essay will take a loo- 25288Murphy2025-03-23
Java Juggernaut: The key to data engineering mastery- 25215Murphy2025-03-23
Parsing complex documents can be easy if you have the rights tools- 27040Murphy2025-03-23
An ongoing Recommendation System series- 21379Murphy2025-03-23
Random Forests came a long way- 29242Murphy2025-03-23
What they are and what they do- 27541Murphy2025-03-23
Exploring the modern wave of machine learning: cutting edge fine tuning- 27527Murphy2025-03-23
Understanding the fundamental building blocks of Transformers.- 23753Murphy2025-03-23
Data Pipelines are series of tasks organised in a directed acyclic graph or "DAG". Historically, these are run on open-source workflow orchestration packages like Airflow or Prefect, and require infrastructure managed by data engineers or platfo- 23241Murphy2025-03-23
A comprehensive guide to SVD with Python examples- 20925Murphy2025-03-23
A crucial method in binary outcome analysis- 25547Murphy2025-03-23
Learn how to properly evaluate the performance of time series models through backtesting- 21385Murphy2025-03-23
Our weekly selection of must-read Editors' Picks and original features- 26303Murphy2025-03-23
Most of your machine-learning tasks will typically be, after the initial exploration phase, packaged into images and deployed to on-premise or cloud servers. This will facilitate the rapid iteration to build the infrastructure supporting the operationalis- 29153Murphy2025-03-23
Don't settle for the defaults!- 23142Murphy2025-03-23
A Beginner-Friendly Introduction to MLOps- 28707Murphy2025-03-23
How does Google Bard handle Python coding tasks?- 22526Murphy2025-03-23
Get some practical experience- 28820Murphy2025-03-23
Use category data type when working with low-cardinality categorical features- 28242Murphy2025-03-23
The Inflation of AI: Is More Always Better? We live in the age of AI! Every day, many new AI tools and ML models are being created, trained, released, and often advertised. When looking at Hugging Face for instance, we see almost 400,000 models available- 23038Murphy2025-03-23
Why is ChatGPT only trained up until 2021?
Learn how to rearrange your code to achieve significant speed improvements.
