BSCS 4-1 - Elective 4 - Midterm Examination - 2023

In the context of Machine Learning, what does the "Data" element refer to?

• The process of training a model

• The mathematical formula used for prediction

• The evaluation metrics used to measure model performance

• The input information used to train and test a model

What does the "Loss Function" element in Machine Learning represent?

• The algorithm used to learn from the data

• The mathematical function that measures the model's performance

• The process of training the model

• The method used to evaluate the model's predictions

Which element of Machine Learning focuses on updating the model's parameters based on the provided data?

• Learning Algorithm

• Model

• Task

• Evaluation

Which element of Machine Learning involves choosing appropriate features from the data?

• Data

• Task

• Learning Algorithm

• Model

Which of the following describes the mathematical function that establishes the connection between input data and output data?

• Training

• Algorithm

• Loss Function

• Model

This concept describes the process of using input data along with corresponding output data to establish a relationship through Machine Learning, which can then be utilized to predict output for new input?

• Unsupervised Learning

• Supervised Learning

• Task

• Model

One of the elements of machine learning that involves identifying the specific objective or goal that needs to be achieved using the available data. It requires asking questions like "What task can be accomplished using the given data?" or "What can be learned from the data?”

• Unsupervised Learning

• Supervised Learning

• Task

• Model

Which element of machine learning is responsible for evaluating the performance of a model by measuring its accuracy in predicting the expected outcome?

• Training

• Algorithm

• Loss Function

• Model

It is a set of multiple numeric features. We use it as an input to the machine learning model for training and prediction purposes.

• Targets

• Features

• Categorical numeric sets

• Feature Vector

Why is machine learning considered a critical and transformative technology that plays a vital role in various aspects of our modern society?

• It enables the automation and optimization of complex tasks, leading to increased efficiency

• It enhances decision-making and strategic planning through advanced analytics and predictive modeling

• It empowers businesses to make data-driven decisions and optimize processes.

• It revolutionizes industries and drives innovation by leveraging advanced algorithms and computational power.