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MACHINE LEARNING
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MACHINE LEARNING
- A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E
Supervised Learning
- Given a set of training data, make predictions based on this previous data
- Regression
- Predict continuous value
- Linear Regression
- Cost Function
- Measure the accuracy of our hypothesis h
- takes an average difference of all the results of the hypothesis with inputs from x's and the actual output y's. (=average difference between guess and actual result)
- Cost Function
- Classification
- Classify value under a category
Unsupervised Learning
- When you don't know the results or have training data, let algorithm find patterns in presented data.
- Clustering
- Non-clustering
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- Information Technology Mind Map on MACHINE LEARNING, created by Joey Wilmots on 07/02/2018.
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- Joey Wilmots
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