Beyond Accuracy: Exploring Exotic Metrics for Holistic Evaluation of Machine Learning Models
Machine learning has undoubtedly become a powerful tool in today's data-driven world, but are we truly tapping into its full potential...- 21511Murphy ≡ DeepGuide
RecList 2.0: Open-Source Systematic Testing of ML Models
A new RecList to provide more flexibility and better support for evaluation- 20191Murphy ≡ DeepGuide
Topic Modelling in production
Leveraging LangChain to move from ad-hoc Jupyter Notebooks to production modular service- 25775Murphy ≡ DeepGuide
We Need to Raise the Bar for AI Product Managers
How to Stop Blaming the 'Model' and Start Building Successful AI Products- 28875Murphy ≡ DeepGuide
The DIY Path to AI Product Management: Picking a Starter Project
Building real-world skills through hands-on trial and error.- 25644Murphy ≡ DeepGuide
Evaluations with Chat Formats
Applying chat templates to generative LM evaluation tests- 23565Murphy ≡ DeepGuide
What Exactly Is an "Eval" and Why Should Product Managers Care?
How to stop worrying and love the data- 26715Murphy ≡ DeepGuide
Evaluating synthetic data
Assessing plausibility and usefulness of data we generated from real data- 24477Murphy ≡ 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