Interpretable Features in Large Language Models
And other interesting tidbits from the new Anthropic Paper- 21818Murphy2025-03-22
A Deep Dive into In-Context Learning
Stepping out of the "comfort zone" - part 2/3 of a deep-dive into domain adaptation approaches for LLMs- 23335Murphy2025-03-22
YOLO – Intuitively and Exhaustively Explained
The genesis of the most widely used object detection models.- 20594Murphy2025-03-22
AI Use Cases are Fundamentally Different
How to find unique use cases for AI and places where moderate AI performance is still valuable- 22997Murphy2025-03-22
Why You Don't Need JS to Make 3D plots
Visualizing crime geodata in python- 24169Murphy2025-03-22
Performance Insights from Sigma Rule Detections in Spark Streaming
Utilizing Sigma rules for anomaly detection in cybersecurity logs: A study on performance optimization- 23921Murphy2025-03-22
PRISM-Rules in Python
A simple python rules-induction system- 24636Murphy2025-03-22
Optimizing Memory Consumption for Data Analytics Using Python – From 400 to 0.1
Reducing the memory consumption of your code means reducing hardware requirements- 29883Murphy2025-03-22
Bit-LoRA as an application of BitNet and 1.58 bit neural network technologies
Abstract: applying ~1bit transformer technology to LoRA adapters allows us to reach comparable performance with full-precision LoRA...- 24082Murphy2025-03-22
How I Use ChatGPT As A Data Scientist
How ChatGPT improved my productivity as a data scientist- 27467Murphy2025-03-22
The Trap of Sprints: Don't Be Like Scarlett O'Hara. Think Today!
Why data scientists should prioritize communication and flexibility in agile projects- 23342Murphy2025-03-22
Comparing Country Sizes with GeoPandas
How to project, shift, and rotate geospatial data- 20262Murphy2025-03-22
Cross-validation with XGBoost – Enhancing Customer Churn Classification with Tidymodels
Step-by-step guide to implementing cross-validation, feature engineering, and model evaluation with XGBoost in Tidymodels- 26925Murphy2025-03-22
Measuring The Intrinsic Causal Influence Of Your Marketing Campaigns
Causal AI, exploring the integration of causal reasoning into machine learning- 24461Murphy2025-03-22
A Deep Dive into Fine-Tuning
Stepping out of the "comfort zone" - part 3/3 of a deep-dive into domain adaptation approaches for LLMs- 30097Murphy2025-03-22
The Meaning of Explainability for AI
Do we still care about how our machine learning does what it does?- 23454Murphy2025-03-22
Linear Attention Is All You Need
Self-attention at a fraction of the cost?- 21274Murphy2025-03-22
ML Engineering 101: A Thorough Explanation of The Error "DataLoader worker (pid(s) xxx) exited
A deep dive into PyTorch DataLoader with Multiprocessing- 23012Murphy2025-03-22
Understanding You Only Cache Once
This blog post will go in detail on the "You Only Cache Once: Decoder-Decoder Architectures for Language Models" Paper and its findings- 23228Murphy2025-03-22
MMM: Bayesian Framework for Marketing Mix Modeling and ROAS
Bayesian framework to model media channels performance, Return on Ad Spend (ROAS), and budget allocation using PyMC- 20607Murphy2025-03-22
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.