Machine Learning: Difference between revisions
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===Regression Problem=== | ===Regression Problem=== | ||
The goal is to predict a | The goal is to predict a continuous value. | ||
===Classification Problem=== | ===Classification Problem=== | ||
Revision as of 00:23, 17 December 2017
Machine Learning
The science of getting computers to learn without being explicitly programmed (Arthur Samuel).
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 (Tom Mitchell)
Neural Networks
Learning algorithms that mimic how the brain works.
Natural Language Processing (NLP)
Learning Algorithms
Supervised Learning
In supervised learning, we have at our disposal a dataset that tell us which is the "correct answer".
Regression Problem
The goal is to predict a continuous value.
Classification Problem
Unsupervised Learning
Reinforcement Learning
Recommender System
Feature
Synonymous with attribute.
- Infinite number of features.