The Little Book of ML Metrics 👀
I'm writing a book on ML metrics.
Hi there, some exciting news. Wojtek Kuberski (NannyML CTO) and I are writing a book on Machine Learning metrics!
Metrics are arguably the most important part of data science work, yet they are rarely taught in courses or university degrees. Even senior data scientists often have only a basic understanding of metrics—literally, almost nobody knows what happens to MAPE if we scale the targets to a standard normal distribution.
I’m hooked. Tell me more…
The idea of the book is to be this little handbook that lives on top of every data scientist's desk for quick reference of the most known metric, ahem, accuracy, to the most obscure thing (looking at you, P4-metric)
What metrics will be included?
The book will cover the following types of metrics:
Regression
Classification
Clustering
Ranking
Vision
Text
GenAI
Bias and Fairness
This list is not set in stone; hit me up if you have any other recommendations!
How do I get a copy?
If you want to support this project and get your own copy, pre-orders are open. They are currently at a 50% discount.
When will this be finished?
We are aiming to start shipping by Q1 2025.
If, for any reason, you would like to cancel your pre-order, you'll get 100% of your money back. No questions asked.
Let me know if you have any questions 🤗