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DC Field | Value | Language |
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dc.contributor.author | Tiwari, Ritwik | - |
dc.contributor.author | Dutta, Vaibhav | - |
dc.contributor.author | Gupta, Pradeep Kumar [Guided by] | - |
dc.date.accessioned | 2022-10-11T10:10:56Z | - |
dc.date.available | 2022-10-11T10:10:56Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7643 | - |
dc.description.abstract | Machine learning is a subset of Artificial Intelligence. It is field where algorithms are designed so that machines can learn autonomously from data. Machine Learning is a sub-set of computerized reasoning where PC calculations are utilized to self-sufficiently gain from information and data. In machine learning PCs don't need to be unequivocally modified however can change and enhance their calculations independent from anyone else. Today, machine learning calculations empower PCs to speak with people, self governing drive vehicles, compose and distribute sport coordinate reports, and discover psychological militant suspects. I immovably trust machine learning will seriously affect most ventures and the employments inside them, which is the reason each director ought to have probably some grip of what machine realizing is and how it is developing. In this post I offer a speedy excursion through time to look at the roots of machine learning and in addition the latest achievements. During the 1950s, we see the principal PC amusement program professing to have the capacity to beat the checkers best on the planet. This program helped checkers players a considerable measure in enhancing their aptitudes! Around a similar time, Frank Rosenblatt concocted the Perceptron which was an, extremely straightforward classifier however when it was joined in vast numbers, in a system, it turned into a ground breaking beast. Indeed, beast is with respect to the time and in that time, it was a genuine leap forward. At that point we see quite a long while of stagnation of the neural system field because of its challenges in tackling certain issues. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Algorithms | en_US |
dc.title | Recommender Systems Algorithms | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Recommender Systems Algorithms.pdf | 1.44 MB | Adobe PDF | View/Open |
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