Introduction to Machine Learning Overview

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What is the main premise of Machine Learning?

It is based on the idea that computers cannot learn from data.

It focuses on making machines less human-like in their behavior.

It allows systems to learn and improve from experience without being explicitly programmed. (correct)

It requires explicit programming for systems to learn and improve from experience.

What is the role of a Machine Learning model?

Executing programs with minimal human intervention.

Collecting and storing training data for future use.

Representing a real-world process with mathematical equations. (correct)

Creating measurable properties or parameters of the dataset.

What is a feature in the context of Machine Learning?

The study of making machines more human-like in their behavior and decisions.

The process of automating machine learning models.

A measurable property or parameter of the dataset. (correct)

A set of multiple numeric features.

What does a feature vector represent in Machine Learning?

A set of multiple numeric features for modeling real-world processes. (D) Signup and view all the answers

How does the learning process in Machine Learning occur?

With little human intervention and automated improvement based on experiences. (D) Signup and view all the answers

What determines the choice of algorithm in Machine Learning?

The type of data at hand and the type of activity that needs to be automated. (B) Signup and view all the answers

What is the role of the training data in a Machine Learning model?

It finds patterns in the input data and trains the model for expected results (A) Signup and view all the answers

What is the consequence of overfitting in a Machine Learning model?

The model fails to characterize the data correctly (A) Signup and view all the answers

What is the purpose of data preparation in a Machine Learning workflow?

To transform raw data into a clean dataset (A) Signup and view all the answers

What determines the type of learning algorithm used in Machine Learning?

The type of problem that needs to be solved and the type of data available (D) Signup and view all the answers

What is the function of a clustering algorithm in Machine Learning?

To create clusters when the data is unlabeled (A) Signup and view all the answers

What impact does the quality and quantity of gathered data have on the accuracy of a Machine Learning system?

It directly affects the accuracy of the desired system (C) Signup and view all the answers

What are some methods of cleaning a dataset during data preparation in a Machine Learning workflow?

Removing instances having missing values from the dataset (C) Signup and view all the answers

What happens if a Machine Learning model fails to decipher the underlying trend in the input data?

The model does not fit the data well enough (C) Signup and view all the answers

Why is it important to divide the dataset into a training dataset and a testing dataset during model training?

To evaluate how well the model performs on unseen data (B) Signup and view all the answers

What is the consequence of underfitting in a Machine Learning model?

The model does not fit the data well enough (D) Signup and view all the answers