Learn how to access the datasets on Hugging Face Hub and how you can load them remotely using DuckDB and the Datasets library- 21337Murphy2025-03-23
Introduction As the El Niño phenomenon intensifies in 2023, climatological and precipitation data have become fundamental in deciphering its impact on weather patterns and climate dynamics in global or regional scales. In terms of precipitation data, two- 22460Murphy2025-03-23
A/B testing is like Jenga, a delicate balance of interconnected pieces that form the foundation of a successful experiment. Just like in the game of Jenga, where removing the wrong block can cause the entire tower to crumble, A/B testing relies on multipl- 29008Murphy2025-03-23
Photo by Iván Díaz on Unsplash With our world becoming more and more digitized, data collection is expanding rapidly. This data has allowed us to create more accurate models that have helped us to solve problems and find optimized solutions in many fields- 20573Murphy2025-03-23
It is Time to Reap The Fruits of Your Hard Marketing Mix Model Training!- 29558Murphy2025-03-23
How Hamilton can help you write more maintainable Airflow DAGs- 24332Murphy2025-03-23
Practical Lessons from Porting range-set-blaze to no_std and WASM- 27002Murphy2025-03-23
ML: all you need to know without any overcomplicated math- 24753Murphy2025-03-23
Learn how to implement custom functions for your LLM, using tools- 26942Murphy2025-03-23
Stop Using PowerPoint for Your ML Presentations and Try This Instead PowerPoint presentations suck. At least, bad ones do. Bad PowerPoints create distracted audiences (who turn off their cameras and multitask), and they make it easy for presenters to get- 22345Murphy2025-03-23
What is this about? New LLMs are released every week, and if you’re like me, you might ask yourself: Does this one finally fit all the use cases I want to utilise an LLM for? In this tutorial, I will share the techniques that I use to evaluate new L- 25942Murphy2025-03-23
Implementing the math in papers into PyTorch / TF code will improve your coding skills and understanding of the workings of deep models.- 20867Murphy2025-03-23
Leveraging ChromaDB, Langchain, and ChatGPT: Enhanced Responses and Cited Sources from Large Document Databases- 24351Murphy2025-03-23
PYTHON TOOLBOX In this article, I will take you into the world of aiomultiprocess, a library that combines the powerful capabilities of Python asyncio and multiprocessing. This article will explain through rich code examples and best practices. By the end- 22341Murphy2025-03-23
A timeline of how I went from being scared of maths to becoming a full-fledged Data Scientist at a renowned Tech firm- 26855Murphy2025-03-23
Named Entity Recognition applied to Dutch news for automatic NE-summaries, research into our recommendation system and new data insights.- 25575Murphy2025-03-23
In the context of database operations, a transaction refers to an operation that is considered to be a single logical unit of work and aims to leave the underlying system in a consistent state. Consistency is maintained by ensuring that all the operations- 29653Murphy2025-03-23
Basics of anomaly detection, its use-cases, and an implementation of simple yet powerful algorithm in Python- 24504Murphy2025-03-23
From finding the right dataset to turning AI green(er)- 21085Murphy2025-03-23
In recent years, Machine Learning has exploded in popularity, and Neural Deep Learning models have blown shallow models like XGBoost [4] out of the water for complex tasks like image and text processing. However, deep models are often less effective than- 22055Murphy2025-03-23
Why is ChatGPT only trained up until 2021?
Learn how to rearrange your code to achieve significant speed improvements.
