40 interview questions on Machine learning - Fundamentals 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

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

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 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

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

Easy

1 vote745 runs0 comment

What type(s) of learning can the following performance indicators be used?

Data Scientist

supervised learning

performance indicators

Martinat Mar 15, 2022

Hard

1 vote292 runs0 comment

Can a deep learning model be modified by hand by the developer? Select the correct statement(s)

Data Scientist

neural network

parameters

Martinat Mar 15, 2022

Easy

1 vote256 runs0 comment

Cross validation is a technique used for evaluating ML or DL (deep learning) models. The method consists in training several models on subsets of the input data and evaluating them on the complementary subset of this same data. It aims at avoiding overfitting.

Data Scientist

overfitting

validation

Martinat Mar 15, 2022

Medium

1 vote204 runs0 comment

Select the true statements about PCA.

Data Scientist

machine learning

dimension reduction

unsupervised learning

Martinat Mar 15, 2022

Easy

1 vote56 runs0 comment

Which code language is the most used to implement machine learning?

Data Scientist

python

machine learning

Martinat Mar 15, 2022

Easy

0 vote764 runs0 comment

The training data set is the set of data the algorithm will learn from. It is used to fit the neural networks’ parameters (weight and bias): the model improvement is performed based on this data set under the gradient descent’s monitoring.

Data Scientist

machine learning

neural networks

gradient descent

Martinat Mar 15, 2022

Easy

0 vote758 runs0 comment

What is the relation between Artificial intelligence (AI), machine learning and deep learning?

Data Scientist

machine learning

deep learning

artificial intelligence

Martinat Mar 15, 2022

40 interview questions on Machine learning - Fundamentalsfor developers (2024)

Test your technical skills before an interview of Machine learning - Fundamentals with 40 corrected questions. 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 ?

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 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?

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.

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.

What type(s) of learning can the following performance indicators be used?

Can a deep learning model be modified by hand by the developer? Select the correct statement(s)

Cross validation is a technique used for evaluating ML or DL (deep learning) models. The method consists in training several models on subsets of the input data and evaluating them on the complementary subset of this same data. It aims at avoiding overfitting.

Select the true statements about PCA.

Which code language is the most used to implement machine learning?

The training data set is the set of data the algorithm will learn from. It is used to fit the neural networks’ parameters (weight and bias): the model improvement is performed based on this data set under the gradient descent’s monitoring.

What is the relation between Artificial intelligence (AI), machine learning and deep learning?