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http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/5927
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DC Field | Value | Language |
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dc.contributor.author | Singh, Dilpreet | - |
dc.contributor.author | Gaur, Abhinav | - |
dc.contributor.author | Bansal, Sakshi | - |
dc.contributor.author | Bhooshan, Sunil Vidya [Guided by] | - |
dc.date.accessioned | 2022-08-22T09:00:15Z | - |
dc.date.available | 2022-08-22T09:00:15Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5927 | - |
dc.description.abstract | Machines having the potential of learning different tasks like human being and perform what's desired from them would like the flexibility to remold gathered task data into their own illustration and spatial property. Different task data that has been no inheritable e.g. with Programming by application example by observant a personality's doesn't a-priori contain any bot-related data and actions, and is outlined within the space and action house of the human act. The objective of this informing is to gift a summary of the machine learning techniques presently in use or in thought at applied math agencies worldwide. Automatic identification and extraction of those algorithmic programs from pedantic digital documents would change automatic algorithm classification, searching, analysis and discovery. AN algorithmic program computer program, that identifies pseudo codes in pedantic documents and makes them searchable, has been enforced as an area of this suite. Coming up with systems typically build the idea that wise world data is out there. Our approach makes a lot of realistic assumption that the initial data regarding the actions is incomplete, and uses experimentation as a learning mechanism once the missing data causes an execution failure. Previous work on learning experimentally has not self-addressed this issue. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Internet of things | en_US |
dc.subject | Python | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Raspberry pi | en_US |
dc.title | Active Learning Intellect Machine Based on Voice Recognition | 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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Active Learning Intellect Machine Based on Voice Recognition.pdf | 2.95 MB | Adobe PDF | View/Open |
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