Prepare for your upcoming machine learning interview by working through these practice questions that span across important topics in machine learning.
Preparing for a Machine Learning (ML) interview could be quite challenging. Where to start? What topics to focus on? Theory or practice? Well, fear not! In this course, you will learn to answer 30 non-trivial questions that often pop up in ML interviews. These questions revolve around seven important topics: data preprocessing, data visualization, supervised learning, unsupervised learning, model ensembling, selection, and evaluation. You will practice these concepts while learning to predict the rating of an Android app or segmenting mall customers based on their purchasing behaviors. Keep in mind -- this course is meant to be more challenging than your average DataCamp course. Make sure to complete your prerequisite courses so you can gain the most out of the topics we will cover!
Preparing for a Machine Learning (ML) interview could be quite challenging. Where to start? What topics to focus on? Theory or practice? Well, fear not! In this course, you will learn to answer 30 non-trivial questions that often pop up in ML interviews. These questions revolve around seven important topics: data preprocessing, data visualization, supervised learning, unsupervised learning, model ensembling, selection, and evaluation. You will practice these concepts while learning to predict the rating of an Android app or segmenting mall customers based on their purchasing behaviors. Keep in mind -- this course is meant to be more challenging than your average DataCamp course. Make sure to complete your prerequisite courses so you can gain the most out of the topics we will cover!
