Mastering Model Interpretability: A Comprehensive Look at Partial Dependence Plots
Knowing how to interpret your model is essential to understand if it is not doing weird stuff. The more you know your model, the less likely you are to be surprised by its behavior when it goes to production. Also, the more domain you have over your model- 23022Murphy ≡ DeepGuide
Deep Dive into PFI for Model Interpretability
Another interpretability tool for your toolbox- 20655Murphy ≡ DeepGuide
Why and How to Achieve Longer Context Windows for LLMs
Language models (LLMs) have revolutionized the field of natural language processing (NLP) over the last few years, achieving...- 23703Murphy ≡ DeepGuide
How Tiny Neural Networks Represent Basic Functions
A gentle introduction to mechanistic interpretability through simple algorithmic examples- 25788Murphy ≡ DeepGuide
A Guide to 21 Feature Importance Methods and Packages in Machine Learning (with Code)
From the OmniXAI, Shapash, and Dalex interpretability packages to the Boruta, Relief, and Random Forest feature selection algorithms- 22542Murphy ≡ DeepGuide
Find Unusual Segments in Your Data with Subgroup Discovery
Patient rule induction method finds 35% better segments than previously reported- 27412Murphy ≡ DeepGuide
How to Interpret GPT2-Small
Mechanistic Interpretability on prediction of repeated tokens- 21990Murphy ≡ DeepGuide
Explainability, Interpretability and Observability in Machine Learning
These are terms commonly used to describe the transparency of a model, but what do they really mean?- 23553Murphy ≡ DeepGuide
FormulaFeatures: A Tool to Generate Highly Predictive Features for Interpretable Models
Create more interpretable models by using concise, highly predictive features, automatically engineered based on arithmetic combinations of...- 29631Murphy ≡ DeepGuide
Sparse AutoEncoder: from Superposition to interpretable features
Disentangle features in complex Neural Network with superpositions- 22748Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag