Evaluation Metrics are What You Need to Define in the Earlier Stage
Last Updated on July 20, 2023 by Editorial Team
Author(s): Edward Ma
Originally published on Towards AI.
Statistics
Photo by Edward Ma on Unsplash
If you do not know how to justify whether model is good or not, it is similar to you want to get something but you do not know what it is. After working as a Data Scientist for a few years, I strongly believe that metrics are very important things to define at the earlier stage.
In this series of stories, I will cover some common metrics we should use when measuring model how good it is. Precision and Mean Squared Error (MSE) may come up immediately when talking about metrics. However, I want to highlight… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Take our 90+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!
Towards AI has published Building LLMs for Production—our 470+ page guide to mastering LLMs with practical projects and expert insights!
Discover Your Dream AI Career at Towards AI Jobs
Towards AI has built a jobs board tailored specifically to Machine Learning and Data Science Jobs and Skills. Our software searches for live AI jobs each hour, labels and categorises them and makes them easily searchable. Explore over 40,000 live jobs today with Towards AI Jobs!
Note: Content contains the views of the contributing authors and not Towards AI.
Related posts
Popular posts
Updates
Recent Posts
