Classification in ML: Lessons Learned From Building and Deploying a Large-Scale Model MLOps Blog Classification is one of the most widely applied areas in Machine Learning. In this article, we will talk about feasible techniques to deal with such a large-scale ML Classification model.
Table of contents
What are some examples of large-scale ML classification models?Lesson 1: Mitigating data sparsity problems within ML classification algorithmsLesson 2: Deep metric learning for classificationLesson 3: Selecting an appropriate loss function to train large-scale classification problemsLesson 4: Measuring the performance of a large-scale classification modelLesson 5: Understanding the common challenges you will face with classification models in productionLesson 6: Best practices to follow while building a pipeline for classification modelsFinal thoughtsSort: