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How to choose a machine learning model

Have you ever thought about how we apply machine learning algorithms to problems in order to analyze, visualize, discover trends and find correlations in data? In this article, I will discuss the common steps of building a machine learning model and how to choose the right model for your data. The inspiration for this article comes from common interview questions that are asked about how to deal with data science issues and why they are chosen.

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Feature selection: importance and method details

In this article, I will share with you some of the methods I studied during the last project led by Fiverr.
You'll get some ideas about the basic methods I've tried and the more complicated methods that get the best results - remove the 60% or more features while maintaining accuracy and achieving higher stability for our model. Sex. I will also share our improvements to the algorithm.