Introduction to Machine Learning
Learning Learning is acquiring new, or modifying existing, knowledge, behaviors, skills, values, or preferences and may involve synthesizing different types of information. The ability to learn is possessed by humans and animals.
Learning
What is Machine Learning? Arthur Samuel (1959). Machine Learning: Field of study that gives computers the ability to learn without being explicitly programmed
Machine Learning Tom Mitchell (1998) Well-posed Learning Problem: A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.
Examples Examples: - Database mining Large datasets from growth of automation/web. E.g., Web click data, medical records, biology, engineering - Applications can’t program by hand. E.g., Autonomous helicopter, handwriting recognition, most of Natural Language Processing (NLP), Computer Vision.
Examples
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Machine Learning Unsupervised Learning Technique of trying to find hidden structure in unlabeled data Supervise Learning Technique for creating a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs.