Choosing a machine learning method to implement data is not the easiest of processes. It is essential to first understand the precise business problem and its objectives. For instance, understanding what needs to be predicted and understanding potential outcomes is critical.
One also needs to know what data should be used to train a model, among other factors. Such considerations help with the framing of a machine learning problem. In this article, we will look at how to frame a machine learning problem correctly.
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⌚Time Stamps⌚
00:00 - Introduction to framing the problem
2:24 - Case study example of Netflix for churn rate
6:23 - Business problem to ML problem
7:08 - Types of problem
12:24 - Current solution
13:33 - Getting data
15:09 - Metrics to measure
17:15 - Online Vs Batch?
19:15 - Check Assumptions
✨ Hashtags✨
#100DaysOfMachineLearning #MachineLearningFullCourse #MachineLearningInHindi
10 июл 2024
