Accéder au contenu principal
AccueilPython

cours

Practicing Machine Learning Interview Questions in Python

Avancé
Actualisé 01/2025
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Commencer le cours gratuitement

Inclus gratuitementPremium or Teams

PythonMachine Learning4 heures16 vidéos60 exercices4,600 XP10,238Déclaration de réalisation

Créez votre compte gratuit

GoogleLinkedInFacebook

ou

En continuant, vous acceptez nos Conditions d'utilisation, notre Politique de confidentialité et le fait que vos données sont stockées aux États-Unis.
Group

Formation de 2 personnes ou plus ?

Essayer DataCamp for Business

Apprécié par les apprenants de milliers d’entreprises

Description du cours

Prepare for Your Machine Learning Interview

Have you ever wondered how to properly prepare for a Machine Learning Interview? In this course, 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.

Practice Answers to the Most Common Machine Learning Interview Questions

By the end of the course, you will possess both the required theoretical background and the ability to develop Python code to successfully answer these 15 questions.

The coding examples will be mainly based on the scikit-learn package, given its ease of use and ability to cover the most important machine learning techniques in the Python language.

The course does not teach machine learning fundamentals, as these are covered in the course's prerequisites.

Conditions préalables

Unsupervised Learning in PythonSupervised Learning with scikit-learn
1

Data Pre-processing and Visualization

Commencer le chapitre
2

Supervised Learning

Commencer le chapitre
3

Unsupervised Learning

Commencer le chapitre
4

Model Selection and Evaluation

Commencer le chapitre
Practicing Machine Learning Interview Questions in Python
Cours
terminé

Earn Déclaration de réalisation

Ajoutez ces informations d’identification à votre profil LinkedIn, à votre CV ou à votre CV
Partagez-le sur les réseaux sociaux et dans votre évaluation de performance

Inclus avecPremium or Teams

S'inscrire maintenant

Inscrivez-vous 15 millions d’apprenants et commencer Practicing Machine Learning Interview Questions in Python Aujourd’hui!

Créez votre compte gratuit

GoogleLinkedInFacebook

ou

En continuant, vous acceptez nos Conditions d'utilisation, notre Politique de confidentialité et le fait que vos données sont stockées aux États-Unis.