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Questions and Answers
What is the main goal of machine learning?
Which type of machine learning does not include desired outputs in the training data?
What is the purpose of a learning algorithm in machine learning?
In machine learning, what does 'bias' refer to?
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Which type of machine learning learns from mistakes and rewards?
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What is the purpose of training data in machine learning?
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Which type of machine learning aims to group similar data points together?
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What is the importance of a trained model in machine learning?
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'Dim.Reduction' in machine learning focuses on reducing what?
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Study Notes
Introduction to Machine Learning
- Machine learning has broad applicability in daily life, including finance, entertainment, natural language processing, information retrieval, computer vision, robotics, healthcare, medicine, and biology.
- There is a close connection between theory and practice, and the field is open to new work, such as deep learning.
What can Machine Learning do?
- Machine learning can make "intelligent" machines that can be "smarter" than humans.
- Examples include IBM's Watson Question Answering system, which beat the Jeopardy champion Ken Jennings at a quiz bowl.
Human Learning Analogy
- Learning in machine learning is similar to human learning, where you expect to learn a subject in a specific course and are judged on your performance on an exam.
- A good exam should test your ability to generalize, not just memorize previous questions.
Predicting the Future
- Machine learning involves predicting the future based on the past.
- Examples include distinguishing a picture of someone from another person or distinguishing cancerous cells from normal cells.
Machine Learning Process
- Learn a classifier from examples to distinguish between two classes.
- Then, predict the class on new examples using what you've learned.
Types of Machine Learning
- Supervised learning: training data includes desired outputs.
- Unsupervised learning: training data does not include desired outputs.
- Reinforcement learning: learn from mistakes and rewards.
- Clustering, dimensionality reduction, association, classification, regression, and ranking are other types of machine learning.
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Description
Explore the foundational concepts of machine learning in Chapter 1 of CMPS 460 course. Learn about the goals, intentions, and broad applicability of machine learning in various fields like finance, entertainment, healthcare, and more.
