Practicing Machine Learning Interview Questions in Python Data Camp

Overview

Context

Have you ever wondered how to properly prepare for a Machine Learning Interview? In this Practicing Machine Learning Interview Questions in Python course offered by Data Camp, you will prepare answers for 15 common Machine Learning (ML) in Python interview questions for a data scientist role.

These questions will revolve around seven important topics: data preprocessing, data visualization, supervised learning, unsupervised learning, model ensembling, model selection, and model evaluation.

Refresh Your Machine Learning Knowledge

You’ll start by working on data pre-processing and data visualization questions. After performing all the preprocessing steps, you’ll create a predictive ML model to hone your practical skills.

Next, you’ll cover some supervised learning techniques before moving on to unsupervised learning. Depending on the role, you’ll likely cover both topics in your machine learning interview.

Finally, you’ll finish by covering model selection and evaluation, looking at how to evaluate performance for model generalization, and look at various techniques as you build an ensemble model.