Martin contributions

121 questions

Medium

10 votes868 runs0 comment

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

Data Scientist

machine learning

missing data

at Apr 4, 2022

Easy

9 votes507 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

Medium

7 votes777 runs0 comment

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

Data Scientist

machine learning

missing data

at 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

at 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

at Mar 15, 2022

Easy

5 votes531 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

Easy

5 votes515 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

5 votes403 runs0 comment

What are the different learning methods used for machine learning ?

Data Scientist

machine learning

learning

at Sep 19, 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

at Mar 15, 2022

Easy

4 votes287 runs0 comment

Which code language is the most used to implement AI?

Data Scientist

python

language

at 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

at 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

at Mar 15, 2022

Easy

3 votes511 runs0 comment

What is ensemble learning? It consists in …

Data Scientist

models

ensemble

at Mar 15, 2022

Medium

3 votes377 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

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

at Mar 15, 2022

Easy

2 votes738 runs0 comment

How to assess a clustering model performances?

Data Scientist

metrics

clustering

at 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

at Mar 15, 2022

Easy

2 votes287 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

2 votes284 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

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

at Dec 13, 2023

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

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

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.

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.

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 ?

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.

Which code language is the most used to implement AI?

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.

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.

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

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

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

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.

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.

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 ?

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.

Which code language is the most used to implement AI?

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.

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.

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

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

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