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Machine Learning Introduction to the Course Nevin L. Zhang lzhang@cse.ust.hk Department of Computer Science and Engineering The Hong Kong University of Science and Technology This set of notes is based on internet resources. Nevin L. Zhang

  1. Machine Learning Introduction to the Course Nevin L. Zhang lzhang@cse.ust.hk Department of Computer Science and Engineering The Hong Kong University of Science and Technology This set of notes is based on internet resources. Nevin L. Zhang (HKUST) Machine Learning 1 / 7

  2. What is Machine Learning? Arthur Samuel (1959): Machine learning is a ”field of study that gives computers the ability to learn without being explicitly programmed ”. Nevin L. Zhang (HKUST) Machine Learning 2 / 7

  3. What is Machine Learning? Arthur Samuel (1959): Machine learning is a ”field of study that gives computers the ability to learn without being explicitly programmed ”. Machine learning is the science of getting machines to learn and act in a similar way to humans while also autonomously learning from real-world interactions and sets of training data that we feed them. Nevin L. Zhang (HKUST) Machine Learning 2 / 7

  4. What is Machine Learning? Arthur Samuel (1959): Machine learning is a ”field of study that gives computers the ability to learn without being explicitly programmed ”. Machine learning is the science of getting machines to learn and act in a similar way to humans while also autonomously learning from real-world interactions and sets of training data that we feed them. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed . Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Nevin L. Zhang (HKUST) Machine Learning 2 / 7

  5. What is Machine Learning? Machine Learning is the science of making computer artifacts improve their performance with respect to a certain performance criterion using example data or past experience , without requiring humans to program their behavior explicitly. Nevin L. Zhang (HKUST) Machine Learning 3 / 7

  6. What is Machine Learning? Machine Learning is the science of making computer artifacts improve their performance with respect to a certain performance criterion using example data or past experience , without requiring humans to program their behavior explicitly. Machine Learning is a set of methods that automatically detect patterns in data , use the uncovered patterns to for prediction or decision making. Nevin L. Zhang (HKUST) Machine Learning 3 / 7

  7. Machine Learning (and AI) is Very Hot Countries and companies invest heavily in ML and AI. Nevin L. Zhang (HKUST) Machine Learning 4 / 7

  8. Machine Learning (and AI) is Very Hot The number of research papers on AI and Machine Learning has been increasing sharply in the past few years. http://aipano.cse.ust.hk/ Overview of topics: http://home.cse.ust.hk/ lzhang/topic/ai-tree.pdf Nevin L. Zhang (HKUST) Machine Learning 5 / 7

  9. Coverage of this Course Objective: Quickly bring students with little background to the forefront of research, while covering all important topics in between. Nevin L. Zhang (HKUST) Machine Learning 6 / 7

  10. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  11. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  12. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  13. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. 4 Why can it achieve its goal? [Theoretical guarantees] (Theoretician) Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  14. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. 4 Why can it achieve its goal? [Theoretical guarantees] (Theoretician) We will focus mostly on the first three questions . Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  15. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. 4 Why can it achieve its goal? [Theoretical guarantees] (Theoretician) We will focus mostly on the first three questions . We will explain the math behind the objective functions and how the steps are derived from principles . Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  16. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. 4 Why can it achieve its goal? [Theoretical guarantees] (Theoretician) We will focus mostly on the first three questions . We will explain the math behind the objective functions and how the steps are derived from principles . So, we will do a fair amount of math derivations. Nevin L. Zhang (HKUST) Machine Learning 7 / 7

  17. Depth of this Course Questions about an ML Algorithm: 1 What does it do? [Inputs and Outputs] (User) 2 How does it work? [Steps] (Programmer) 3 Why does it work the way it does? (Algorithm Designer) Ideas behind the steps. Pros and cons w.r.t alternatives. 4 Why can it achieve its goal? [Theoretical guarantees] (Theoretician) We will focus mostly on the first three questions . We will explain the math behind the objective functions and how the steps are derived from principles . So, we will do a fair amount of math derivations. Hands-on experiences are to be gained via self-practice, programming assignment and term project. Nevin L. Zhang (HKUST) Machine Learning 7 / 7

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