COSC-E4 CS Elective 4 (Machine Learning) - Lesson 1: Introduction
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Questions and Answers

What is the primary purpose of using machine learning algorithms?

  • To provide quality data for the models to operate efficiently
  • To scale to handle larger problems and technical questions
  • To transform processes that were previously only possible for humans to perform (correct)
  • To continuously improve data analysis over time
  • Which of the following is NOT a common example of machine learning applications?

  • Predicting natural disaster locations and timelines
  • Reviewing resumes for everyday businesses
  • Image detection for self-driving cars
  • Analyzing financial data for stock trading (correct)
  • What is the primary reason why 'quality data' is necessary for machine learning models to operate efficiently?

  • To transform processes that were previously only possible for humans
  • To ensure the model can continuously improve itself over time
  • To scale the model to handle larger problems and technical questions
  • To provide the necessary training and validation datasets (correct)
  • Which component is NOT a part of the definition of learning?

    <p>Motivation as the driving force behind the change</p> Signup and view all the answers

    What is the key component of a dataset that all instances (rows) share?

    <p>A common attribute</p> Signup and view all the answers

    Which of the following is the LEAST important factor in ensuring machine learning models perform well?

    <p>The scale and complexity of the problems the model can handle</p> Signup and view all the answers

    Which term is used to describe learning as 'the transformative process of taking in information that, when internalized and mixed with what we have experienced—changes what we know and builds on what we do'?

    <p>Experiential learning</p> Signup and view all the answers

    What is the primary purpose of using validation (or testing) datasets in machine learning?

    <p>To ensure the machine learning model is interpreting the training data accurately</p> Signup and view all the answers

    Which author is referenced for defining learning as 'the transformative process of taking in information' in the text?

    <p>No author is referenced</p> Signup and view all the answers

    What type of change characterizes learning?

    <p>Permanent changes due to experience</p> Signup and view all the answers

    Which aspect is considered as the cause of the change in learning according to the text?

    <p>Experience in the environment</p> Signup and view all the answers

    Based on the text, what does learning not depend on for the change to occur?

    <p>Motivation</p> Signup and view all the answers

    What are the two key values that the linear regression algorithm needs to learn?

    <p>m and b</p> Signup and view all the answers

    In the Machine Learning process, what is the purpose of testing the model against previously unseen data?

    <p>To measure the objective performance of the model</p> Signup and view all the answers

    Why is it important to have a good train/eval split in Machine Learning?

    <p>To avoid overfitting</p> Signup and view all the answers

    What metric is used in Machine Learning to measure the objective performance of a model?

    <p>Combination of metrics on test data</p> Signup and view all the answers

    Which font is specified for the header in the presentation using Open Sans?

    <p>Open Sans SemiBold</p> Signup and view all the answers

    What is the purpose of using previously unseen data in Machine Learning model evaluation?

    <p>To fine-tune the model</p> Signup and view all the answers

    What is the primary purpose of a machine learning algorithm when building a machine learning model?

    <p>To find patterns in the input data and train the model for expected results</p> Signup and view all the answers

    Which of the following is NOT a common terminology used in the context of machine learning models?

    <p>Overstuffing</p> Signup and view all the answers

    What is the key difference between overfitting and underfitting in the context of machine learning models?

    <p>Overfitting occurs when the model is too complex, while underfitting occurs when the model is too simple</p> Signup and view all the answers

    What is the purpose of the 'target' or 'label' in a machine learning model?

    <p>The value that the machine learning model has to predict</p> Signup and view all the answers

    What is the primary objective of supervised learning?

    <p>To predict continuous values</p> Signup and view all the answers

    Which of the following is an example of an unsupervised learning task?

    <p>Generating tweets similar to those of the US President</p> Signup and view all the answers

    Which of the following is not a characteristic of a machine learning model?

    <p>A model that is suitable for all tasks</p> Signup and view all the answers

    What is the purpose of a loss function in machine learning?

    <p>To evaluate how well the algorithm models the data</p> Signup and view all the answers

    Which of the following is a key difference between supervised and unsupervised learning?

    <p>Supervised learning uses labeled data, while unsupervised learning uses unlabeled data</p> Signup and view all the answers

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