Summary
Chapters
Video Info
Summary
Dr. Chirag Shah, PhD, explains basic machine learning, using optical character recognition and self-driving cars as examples. Types of machine learning—supervised, unsupervised, and reinforced—are clearly explained and illustrated using housing markets, cancer diagnoses, cocktail parties, and social networks as examples.
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Chapter 1: What is Machine Learning?
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Chapter 2: Learning: A Relationship between Experience, Tasks, and Performance
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Chapter 3: Machine Learning: Optical Character Recognition (OCR)
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Chapter 4: Machine Learning: Self-Driving Car
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Chapter 5: Supervised Learning: Linear Regression—Housing Market Example
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Chapter 6: Supervised Learning: Classification—Cancer Diagnosis Example
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Chapter 7: Unsupervised Learning: Cocktail Party Effect Example
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Chapter 8: Unsupervised Learning: Social Network Example
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Chapter 9: Reinforced Learning: Positive or Negative Feedback
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Chapter 10: Limitations in Machine Learning and Summary
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