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Definition What is machine learning Why machine learning is important Generalization Other learning techniques
Machine learning, a branch of artificial intelligence, which concerns about the construction and study of systems that can be learn from data.
•Automating automation •Getting computers to program themselves •Writing software which is the bottleneck Let the data do the work instead!
•Some tasks cannot be defined well, except by examples (e.g., recognizing people). •Relationships and correlations can be hidden within large amounts of data. Machine Learning/Data Mining may be able to find these relationships. •Human designers often produce machines that do not work as well as desired in the environments in which they are used.
Machine learning algorithms can be sorted out dependent on the ideal result of the calculation or the kind of info accessible amid preparing the machine
1. Supervised learning algorithms are prepared on marked models, i.e., input where the ideal yield is known.
2. Unsupervised learning algorithms work on unlabelled precedents, i.e., input where the ideal yield is obscure.
3. Semi-administered learning joins both marked and unlabelled guides to produce a fitting capacity or classifier.
4. Reinforcement learning is worried about how keen specialists should act in a domain to expand some thought of remuneration from grouping of activities Other calculations are: Learning to learn Developmental learning Transduction and so on.
1. Artificial neural networks 2. Inductive programming 3. Support vector machines 4. Bayesian networks 5. Reinforcement learning 6. Association Rule learning 7. Clustering
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