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AI-900: Feature Selection vs Feature Engineering vs Model Training

Learn the difference between feature selection, feature engineering, and model training.


Let’s suppose you are working on an Al application that should predict the weather. From the dataset you have, you want to pick temperature and pressure to train the model. Which machine learning task enables you to do that?

A. Feature selection
B. Model training
C. Feature engineering


A. Feature selection


Feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model.

The correct answer to the question is A. Feature selection. Feature selection is the process of choosing a subset of relevant features from the original dataset that can improve the performance and efficiency of the machine learning model. In this case, temperature and pressure are two features that are likely to have a strong correlation with the weather, so selecting them can help the model make better predictions.

Feature engineering, on the other hand, is the process of creating new features from the existing ones by applying some transformations or calculations. For example, one could create a new feature called humidity by dividing the water vapor pressure by the atmospheric pressure. Feature engineering can also improve the model’s performance, but it is not the same as feature selection.

Model training is the process of fitting the machine learning model to the data by adjusting its parameters using a learning algorithm. Model training requires a set of features and labels (the target variable) as inputs, and it outputs a trained model that can make predictions on new data. Model training is not the task of picking features from the dataset, but rather using them to train the model.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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