Intelligent and Deep Learning Collaborative method for E-Learning Educational Platform using TensorFlow
Main Article Content
Abstract
Nowadays, online learning is platforms are played important role for all the communities. Sitting one place accessing whole world and share their contents through internet media such as webinars, social media, etc. In this paper, we use deep learning method to analyse E-learning platforms using Google TensorFlow. In this model has processing natural language data, convolution neural network and recurrent neural network models. We have identified the clustering of E-learning platforms using content wise, domain wise and selection wise in which we can easily apply association rule mining for identifying prioritization. Those who are accessing the E-learning platforms can be collected and apply Apriori algorithm is used for clustering. We used semantic method for combination of cluster and association rule finding score. In this approach we give prediction result for which platform are used more useful of learning community and gives comparative study of various learning systems. The result is evaluated by using TensorFlow and compares the performance.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.