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Machine Learning

Machine Learning

Machine Learning:

Analytics in which computers "learn" from data to produce models or rules that apply to those data and to other similar data. Predictive modeling techniques such as neural nets, classification and regression trees (decision trees), naive Bayes, k-nearest neighbor, and support vector machines are generally included. One characteristic of these techniques is that the form of the resulting model is flexible, and adapts to the data. Statistical modeling methods that have highly structured model forms, such as linear regression, logistic regression and discriminant analysis are generally not considered part of machine learning. Unsupervised learning methods such as association rules and clustering are also considered part of machine learning.

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Predictive Analytics 1 – Machine Learning Tools
This course introduces to the basic concepts in predictive analytics to visualize and explore data to understand the two core paradigms that account for most business applications of predictive modeling: classification and prediction.
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