You trained a machine learning model, validated its performance across several metrics which are looking good, you put it in production, and then something unforeseen happened (a pandemic like COVID-19...
Category: Model evaluation
How to Track Machine Learning Model Metrics in Your Projects
It is crucial to keep track of evaluation metrics for your machine learning models to: understand how your model is doingbe able to compare it with previous baselines and ideasunderstand...
Tabular Data Binary Classification: All Tips and Tricks from 5 Kaggle Competitions
In this article, I will discuss some great tips and tricks to improve the performance of your structured data binary classification model. These tricks are obtained from solutions of some...
Keras Metrics: Everything You Need To Know
Keras Metrics: Everything You Need To Know Keras metrics are functions that are used to evaluate the performance of your deep learning model. Choosing a good metric for your problem...
F1 Score vs ROC AUC vs Accuracy vs PR AUC: Which Evaluation Metric Should You Choose?
F1 Score vs ROC AUC vs Accuracy vs PR AUC: Which Evaluation Metric Should You Choose? PR AUC and F1 Score are very robust evaluation metrics that work great for...
24 Evaluation Metrics for Binary Classification (And When to Use Them)
24 Evaluation Metrics for Binary Classification (And When to Use Them) Not sure which evaluation metric you should choose for your binary classification problem? After reading this blog post you...
