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How to handle missing data in a given training data set ? (which of the following method can be used)
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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?5
What is ensemble learning? It consists in …16
How to handle missing data in a given training data set ?7
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.4
What are the differences/similarities between a loss function, an error function, and a cost function?6
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.4
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.