Martin contributions

121 questions

Hard

16 votes1048 runs0 comment

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

Data Scientist

machine learning

missing data

at Apr 4, 2022

Medium

12 votes687 runs0 comment

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

Data Scientist

machine learning

deep learning

at Sep 19, 2022

Easy

9 votes708 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

overfitting

at Mar 14, 2022

Medium

8 votes946 runs0 comment

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

Data Scientist

machine learning

missing data

at Apr 4, 2022

Easy

7 votes1018 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

at Mar 15, 2022

Easy

6 votes695 runs0 comment

Given a neural network with 4 inputs, how many connections could exist between the input layer and the first hidden layer?

Data Scientist

neural network

connections

at Apr 4, 2022

Easy

6 votes494 runs0 comment

What are the different learning methods used for machine learning ?

Data Scientist

machine learning

learning

at Sep 19, 2022

Medium

4 votes463 runs0 comment

Fuzzy logic is a method of reasoning used in AI that aims at reproducing human reasoning. The outcome is the opposite of the boolean outcome (binary) . It can be any value between 0 and 1 (true and false). For example, the outcome can be possibly yes (0.7), not sure (0,6) , possibly no (0,4), or certainly no (0,18)...

Data Scientist

logic

reasoning

at Mar 15, 2022

Easy

4 votes353 runs0 comment

Which code language is the most used to implement AI?

Data Scientist

python

language

at Mar 15, 2022

Hard

3 votes391 runs0 comment

Strong AI, also known as general AI, aims at creating smart machines that are indistinguishable from the human brain.

Data Scientist

strong AI

weak AI

at Mar 15, 2022

Easy

3 votes353 runs0 comment

A model hyper-parameter is a configuration which is external to the model. It defines the model’s structure.

Data Scientist

hyperparameters

neural networks

at Mar 15, 2022

Easy

3 votes347 runs0 comment

Supervised learning is a type of machine learning that uses labeled data to train a model.

Data Scientist

supervised learning

machine learning

at Mar 15, 2022

Expert

2 votes915 runs0 comment

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

Data Scientist

reinforcement learning

machine learning

at Apr 4, 2022

Martin

Easy

6 votes973 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

at Mar 15, 2022

Easy

5 votes628 runs0 comment

What is ensemble learning? It consists in …

Data Scientist

models

ensemble

at Mar 15, 2022

Hard

4 votes927 runs

1 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

at Mar 15, 2022

Easy

4 votes922 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

at Mar 15, 2022

Easy

4 votes884 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

at Mar 15, 2022

Medium

3 votes984 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

at Mar 15, 2022

Medium

3 votes896 runs0 comment

How to assess a clustering model performances?

Data Scientist

metrics

clustering

at Mar 15, 2022

Martin

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

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

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.

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.

Given a neural network with 4 inputs, how many connections could exist between the input layer and the first hidden layer?

What are the different learning methods used for machine learning ?

Which code language is the most used to implement AI?

Strong AI, also known as general AI, aims at creating smart machines that are indistinguishable from the human brain.

A model hyper-parameter is a configuration which is **external to the model**. It defines the model’s structure.

Supervised learning is a type of machine learning that uses labeled data to train a model.

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

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.

What is ensemble learning? It consists in …

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?

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.

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?

A model hyper-parameter is a configuration which is external to the model. It defines the model’s structure.