You can’t improve it if you don’t measure it.

A product's success and quality are only as good as metrics that verify it. The Daily Pick A newsletter by Towards Data Science September 28, 2020  •  2 min read  •  View in browser Photo by Stephen Dawson on Unsplash The Definitive Guide to Designing Product Metrics Discussing Precision and Recall metrics, metric design interviews, and the metric lifecycle By Zachary Thomas in Editors' Picks — 11 min read Food photo created by valeria_aksakova — www.freepik.com A Must-Know New Clustering Algorithm for Disease Modelling This article explains a new method for clustering disease data by both subtype and stage called SuStaIn (Subtype & Stage Inference). It explains the concept, summarises the maths, and provides a link to the python code. By Lucy Rothwell in Unsupervised Learning — 10 min read Photo by Valentin Salja on Unsplash Systematically Tuning Your Model by Looking at Bias and Variance Have you ever wondered if there is a more systematic way of tuning your model, than blindly guessing the hyperparameters or using a grid search? By Sebastian Poliak in Computer Science — 4 min read Photo by Clément H on Unsplash A Beginners Guide to Scikit-Learn Getting started with the number one python machine learning library By Rebecca Vickery in Getting Started — 5 min read Photo by Dan Freeman on Unsplash 20 Popular Machine Learning Metrics. Part 2: Ranking, & Statistical Metrics A brief introduction to the most important metrics used in machine learning for evaluating classification, regression, ranking, statistical, vision, NLP, & deep learning models By Shervin Minaee — 8 min read From The Daily Pick A newsletter by Towards Data Science Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday. Make learning your daily ritual. More from this newsletter View in browser

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