Collective Learning Ambiance of Human Pursuance with Intelligent Revival and Prediction Analysis

K. Tharageswari, Laxmi Raja, D. Selvapandian, R. Dhanapal
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Abstract

The work that has been taken enforces the artificial intelligent technique in providing framework to design and make calculations based upon the discovers made by following the examples in learning technology to make a relationship successful for the appraisal of the work done with the enormous amount of information shared using collective learning ambience. The Collective learning ambience will be help for the larger team members for a problem in real time world and bring out a solution for the same. Visualizing these organized work flow in a multilayered frame work gives more difficulties in finding out a perfect solution. So to make the process much easier we are going to use a technique that deals around the machine learning framework in obtaining the required data and fulfill the information gathering as an easy process which is to be taken place in the collective learning ambience(CLA). After which the data and information that has been obtained enhanced with the integration technique in finding out the psychometric analysis and deep learning techniques to figure out feature extraction, skill recognition, pattern finding and also finding out the behaviors in human begin based upon the input that has been obtained from various resources. Thereafter the process will also be helpful in finding out the lower level process involved in the learning process.
人类追求的集体学习氛围与智能复兴与预测分析
所做的工作加强了人工智能技术在提供框架来设计和计算的基础上,通过遵循学习技术中的示例所做的发现,使一种关系成功地用于评估使用集体学习环境共享的大量信息所完成的工作。集体学习的氛围将有助于更大的团队成员在现实世界中的问题,并提出解决方案。将这些有组织的工作流程可视化到一个多层框架中会给找到一个完美的解决方案带来更多的困难。因此,为了使这个过程更容易,我们将使用一种技术来处理机器学习框架,以获得所需的数据,并将信息收集作为一个简单的过程,这将在集体学习环境(CLA)中进行。之后,利用整合技术对所获得的数据和信息进行增强,发现心理测量分析和深度学习技术,从从各种资源中获得的输入开始进行特征提取、技能识别、模式发现和人类行为发现。此后,该过程也将有助于找出学习过程中涉及的较低层次过程。
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