96 interview questions for developers (2026)

Medium

21 votes1585 runs0 comment

How to handle missing data in a given training data set ?

Data Scientist

machine learning

missing data

Martinat Apr 4, 2022

Medium

12 votes1435 runs0 comment

How to handle missing data in a given training data set ?

Data Scientist

machine learning

missing data

Martinat Apr 4, 2022

Easy

12 votes1040 runs0 comment

How is the error calculated during back propagation in a neural network?

Data Scientist

neural network

back propagation

Anonymous authorat Apr 6, 2022

Medium

11 votes1538 runs0 comment

The validation set is used to provide frequent and unbiased evaluations of the model’s fit on the training set while tuning its hyperparameters/parameters: in other words,the model is found and then tested on the validation set before to be improved once again.

Data Scientist

hyperparameters

model

Martinat Mar 15, 2022

Hard

8 votes1410 runs

2 comments

What are the differences/similarities between a loss function, an error function, and a cost function?

Data Scientist

loss function

error function

cost function

Martinat Mar 15, 2022

Easy

7 votes1452 runs0 comment

What is the missing word in the following sentence: Overfitting is the production of a model that corresponds too closely to the training data set and may therefore fail to fit other data sets and so fail to perform any reliable forecast.

Data Scientist

machine learning

overfitting

Martinat Mar 15, 2022

Easy

7 votes1318 runs0 comment

Clustering is an unsupervised machine learning process which aims at automatically discovering natural grouping in the input data. When using this method, the developer is able to choose the number of groups he wants to create.

Data Scientist

machine learning

unsupervised learning

Martinat Mar 15, 2022

Easy

7 votes961 runs0 comment

What is ensemble learning? It consists in …

Data Scientist

models

ensemble

Martinat Mar 15, 2022

Medium

6 votes1339 runs0 comment

How to assess a clustering model performances?

Data Scientist

metrics

clustering

Martinat Mar 15, 2022

Easy

5 votes1469 runs0 comment

Given a data set, which elements will help you to choose what model / machine learning method to use to create an efficient model?

Data Scientist

data

model

Martinat Mar 15, 2022

Easy

5 votes1371 runs0 comment

In order to get good results when implementing deep learning, one needs to prepare his data before using it. What action should be done during this preparation?

Data Scientist

data

preprocessing

Martinat Mar 15, 2022

Easy

5 votes1313 runs0 comment

How to define supervised learning? In supervised learning, the machine trains the model using a labeled training data set.

Data Scientist

supervised learning

machine learning

Martinat Mar 15, 2022

Easy

5 votes984 runs0 comment

In the context of NLP, what is the role of the Stemming method?

Data Scientist

nlp

stemming

Anonymous authorat Apr 6, 2022

Easy

5 votes939 runs1 comment

What does the Soft Margin version of SVMs do?

Data Scientist

machine learning

svm

Anonymous authorat Apr 6, 2022

Easy

5 votes907 runs1 comment

What type of data is PCA (principal component analysis) applied to?

Data Scientist

data

machine learning

Anonymous authorat Apr 6, 2022

Medium

4 votes1388 runs1 comment

Which of the following actions can be used during the date pre-processing when performing regression or classification?

Data Scientist

data

preprocessing

Martinat Dec 13, 2023

Medium

4 votes1385 runs0 comment

Which of the following statements is true when considering machine learning?

Data Scientist

machine learning

artificial intelligence

computer science

Martinat Mar 15, 2022

Easy

4 votes889 runs0 comment

SVMs seek to find a hyperplane that maximizes the width of the separating band between data of different classes.

Data Scientist

machine learning

svm

Anonymous authorat Apr 6, 2022

Hard

4 votes871 runs0 comment

How are the layers of an MLP type neural network connected to each other?

Data Scientist

neural networks

linear

Anonymous authorat Apr 6, 2022

Hard

3 votes1386 runs0 comment

How to define reinforcement learning? Select the sentence that defines best this learning method.

Data Scientist

reinforcement learning

machine learning

Martinat Apr 4, 2022

96 interview questionsfor developers (2026)

Test your developer skills before an interview with 96 corrected questions on 80+ topics. Beginner, Intermediate or Expert level.

How to handle missing data in a given training data set ?

How to handle missing data in a given training data set ?

How is the error calculated during back propagation in a neural network?

The validation set is used to provide frequent and unbiased evaluations of the model’s fit on the training set while tuning its hyperparameters/parameters: in other words,the model is found and then tested on the validation set before to be improved once again.

What are the differences/similarities between a loss function, an error function, and a cost function?

What is the missing word in the following sentence: Overfitting is the production of a model that corresponds too closely to the training data set and may therefore fail to fit other data sets and so fail to perform any reliable forecast.

Clustering is an unsupervised machine learning process which aims at automatically discovering natural grouping in the input data. When using this method, the developer is able to choose the number of groups he wants to create.

What is ensemble learning? It consists in …

How to assess a clustering model performances?

Given a data set, which elements will help you to choose what model / machine learning method to use to create an efficient model?

In order to get good results when implementing deep learning, one needs to prepare his data before using it. What action should be done during this preparation?

How to define supervised learning? In supervised learning, the machine trains the model using a labeled training data set.

In the context of NLP, what is the role of the Stemming method?

What does the Soft Margin version of SVMs do?

What type of data is PCA (principal component analysis) applied to?

Which of the following actions can be used during the date pre-processing when performing regression or classification?

Which of the following statements is true when considering machine learning?

SVMs seek to find a hyperplane that maximizes the width of the separating band between data of different classes.

How are the layers of an MLP type neural network connected to each other?

How to define reinforcement learning? Select the sentence that defines best this learning method.