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Martin
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121 questions
Medium
19 votes1466 runs0 comment

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

Data Scientist
machine learning
missing data
Martinat Apr 4, 2022
Easy
16 votes863 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
Martinat Mar 14, 2022
Easy
16 votes837 runs0 comment

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

Data Scientist
machine learning
deep learning
Martinat Sep 19, 2022
Easy
11 votes1422 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
Medium
10 votes1326 runs0 comment

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

Data Scientist
machine learning
missing data
Martinat Apr 4, 2022
Easy
8 votes844 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
Martinat Apr 4, 2022
Easy
8 votes744 runs0 comment

What are the different learning methods used for machine learning ?

Data Scientist
machine learning
learning
Martinat Sep 19, 2022
Easy
7 votes1344 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
Medium
7 votes716 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
Martinat Mar 15, 2022
Easy
6 votes891 runs0 comment

What is ensemble learning? It consists in …

Data Scientist
models
ensemble
Martinat Mar 15, 2022
Hard
5 votes1300 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
5 votes1223 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
5 votes778 runs0 comment

Which of the following processes are machine learning ones but not particularly related to deep learning?

Data Scientist
machine learning
random forest
Martinat Mar 14, 2022
Easy
5 votes563 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
Martinat Mar 15, 2022
Easy
5 votes563 runs0 comment

Which code language is the most used to implement AI?

Data Scientist
python
language
Martinat Mar 15, 2022
Easy
4 votes1360 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
4 votes1274 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
Medium
4 votes1242 runs0 comment

How to assess a clustering model performances?

Data Scientist
metrics
clustering
Martinat Mar 15, 2022
Easy
4 votes1219 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
4 votes756 runs0 comment

Cross validation is a technique used for evaluating DL (deep learning) models (an ML models in general). 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 Apr 4, 2022