The term known as on which the machine learning algorithms build a model based on sample data is called "Training Data".

Here are the steps to understand this:

1. In machine learning, algorithms are used to make predictions or decisions without being explicitly programmed to perform the task.

2. These algorithms are designed to learn from a dataset that we provide. This dataset is known as "Training Data".

3. The training data is a set of examples used for learning - to fit the parameters of the model.

4. The model tries to learn the patterns, relationships, or features within this training data.

5. Once the model is trained on this data, it can start making predictions or decisions when new data is given to it.

6. Therefore, the term "Training Data" is the foundation on which machine learning algorithms build a model.

Question

The term known as on which the machine learning algorithms build a model based on sample data is called "Training Data".

Here are the steps to understand this:

1. In machine learning, algorithms are used to make predictions or decisions without being explicitly programmed to perform the task.

2. These algorithms are designed to learn from a dataset that we provide. This dataset is known as "Training Data".

3. The training data is a set of examples used for learning - to fit the parameters of the model.

4. The model tries to learn the patterns, relationships, or features within this training data.

5. Once the model is trained on this data, it can start making predictions or decisions when new data is given to it.

6. Therefore, the term "Training Data" is the foundation on which machine learning algorithms build a model.

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