95 interview questions for developers (2024)

Medium

10 votes868 runs0 comment

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

Data Scientist

machine learning

missing data

Martinat Apr 4, 2022

Medium

7 votes777 runs0 comment

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

Data Scientist

machine learning

missing data

Martinat Apr 4, 2022

Easy

6 votes659 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

Easy

5 votes843 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

Easy

5 votes814 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

4 votes734 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

4 votes575 runs1 comment

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

Data Scientist

data

machine learning

Anonymous authorat Apr 6, 2022

Medium

3 votes766 runs0 comment

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

3 votes765 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

3 votes619 runs0 comment

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

Data Scientist

nlp

stemming

Anonymous authorat Apr 6, 2022

Hard

3 votes538 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

Easy

3 votes511 runs0 comment

What is ensemble learning? It consists in …

Data Scientist

models

ensemble

Martinat Mar 15, 2022

Easy

2 votes810 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

2 votes738 runs0 comment

How to assess a clustering model performances?

Data Scientist

metrics

clustering

Martinat Mar 15, 2022

Easy

2 votes735 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

2 votes556 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

2 votes537 runs0 comment

What is the role of assembly function in an artificial neuron?

Data Scientist

neural network

activation function

Anonymous authorat Apr 6, 2022

Medium

2 votes516 runs0 comment

What is the definition interval of the silhouette coefficient?

Data Scientist

machine learning

clustering

Anonymous authorat Apr 6, 2022

Medium

1 vote757 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

Expert

1 vote750 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

95 interview questionsfor developers (2024)

Test your developer skills before an interview with 95 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 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 type of data is PCA (principal component analysis) applied to?

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

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?

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

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

What is ensemble learning? It consists in …

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

How to assess a clustering model performances?

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

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

What is the role of assembly function in an artificial neuron?

What is the definition interval of the silhouette coefficient?

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

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