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Titlebook: Reverse Hypothesis Machine Learning; A Practitioner‘s Per Parag Kulkarni Book 2017 Springer International Publishing AG 2017 Intelligent Sy

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楼主: Callow
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Systemic Machine Learning associate with different scenarios to build context. In different contexts, same information can lead to different out come and can help in producing different possibilities. In linguistic sense same word may have different meanings as per context.
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Reinforcement and Deep Reinforcement Machine LearningData Sciences emerged out of that. The data is collected from various sources. It is collected from big hospitals, data repositories, from cookies running in your machines, intelligent applications running in your devices. It can be crowd sourcing, intelligent crowd sourcing, cognitive data sharing,
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Understanding Machine Learning Opportunitiesmation and retrieving the information timely. It was more like information acquisition to information retrieval. Let us take an example of a student who claims that he learned deep learning. What does that mean? Does he understand the concept or just few terminologies? Can he apply these concepts? Can he expand these concepts?
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Co-operative and Collective Learning for Creative ML learning is a concept where there is an ensemble of learners and based on algorithm it is used. Ensemble learner has more than one learner—even boosting is a concept where more than one learner is learning. Sometimes a set of weak classifiers is used for building strong classifier.
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