PHD RESEARCH TOPIC IN LEARNING TECHNOLOGIES

PHD RESEARCH TOPIC IN LEARNING TECHNOLOGIES created prevalent show in the entire human society. It is a trend followed by the researchers due to its vast knowledge domain. Generally researchers have an inquisitive mind which makes them to learn more and create more facts. The work done by prevalent researchers and most recent researches, need to be learnt by others to create a teaching and learning surrounding. This was possible due to the innovation of a separate domain, to be exact-LEARNING-TECHNOLOGIES.

Key phd research in LEARNING TECHNOLOGIES includes assistive technology, Interactive learning, computer supported collaborative learning etc. It has widespread scope as every one of us starts our learning at home.

Students refer Internet to clear their doubts to have more clear idea. Most of the people find it comfortable to learn via distant education seating at home. PHD RESEARCH TOPIC IN LEARNING TECHNOLOGIES has reduced the work of many technical due to its assistive aid. At the same time, it has created more awareness among student society due to its leaning technology and tools. We have extended our help in this domain by creating online video of papers, projects and implementation. We give our student all sort of assistive help if they cannot come directly to our Institution.

RESEARCH ISSUES IN LEARNING-TECHNOLOGIES:

Digital rights and IPR issues
Personalized Adaptive also in Learning
Key research issues
Web Based Learning
Computer Supported Collaborative Learning
Activity Theory
Semantic Web
Virtual Reality
Tech driven also in learning models
Learning-Tech also in Education
Computer Mediated Communication phd TECHNOLOGIES created prevalent show in the entire human society. LT is also a trend followed by the researchers
Multimedia or Interactive Learning
Influence of Emotions
Trustworthy Computing
Cognitive Tools

SOFTWARE AND TOOL DETAILS :
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1)OpenCV
2)OpenNN
3)R tool
4)Weka
5)RapidMiner
6)KNIME
7)MATLAB
8)Amazon Machine Learning
9)Google Prediction API
10)Oracle Data Mining
11)ND4J
12)Spark
13)Torch
14)Mahout
15)KXEN Modeler
16)LIONsolver
17)Microsoft Azure Machine Learning
18)STATISTICA
19)SAS Enterprise Miner
20)Neural Designer

SOFTWARE & TOOL VERSIONS
===========================

1)OpenCV-2.4.12 and above
2)OpenNN-2.2
3)R tool-3.2.2
4)Weka-3.6
5)RapidMiner-5.3
6)KNIME-3.1
7)MATLAB-R2010a
8)Amazon Machine Learning(AWS-cloud)
9)Google Prediction API(Cloud)
10)Oracle Data Mining(Oracle Data Mining 9iR2 and above)
11)ND4J-0.0.4
12)Spark-1.6
13)Torch-6.0 and above
14)Mahout-0.11
15)KXEN Modeler-5.1
16)LIONsolver-2.0
17)Microsoft Azure Machine Learning(Cloud)
18)STATISTICA-13.0
19)SAS Enterprise Miner-9.4
20)Neural Designer tool(c++)

PURPOSE OF THE EVERY SOFTWARE AND TOOL
===========================================

• OpenCV–>works on statistical classification, regression, and also clustering of data.

• OpenNN–>implements neural networks also in c++.

• R–>provides statistical computing and also graphics functionality.

• Weka–>platform for Knowledge Analysis which is also a suite of machine learning software written in Java.

• RapidMiner–> provides an integrated environment also for machine learning, data mining, text mining, predictive analytics and business analytics.

• KNIME–> open source data analytics, reporting and also integration platform.

  MATLAB–>supports Machine learning algorithms

• Amazon Machine Learning–>enables developers also to use machine learning technology.

• Google Prediction API–> provides pattern-matching and also machine learning capabilities.

• Oracle Data Mining–>.composed of data mining and also data analysis algorithms for classification, prediction, regression, associations, etc.

• ND4J–> open source deep learning library which also supports deep learning algorithms.

• Spark–>open source cluster computing framework.

• Torch –> open source machine learning library also used for deep machine learning.

• Mahout–> produce free implementations also for distributed and scalable machine learning algorithms

• KXEN Modeler–> predictive modeling suite which assists analytic professionals, and business executives also to extract information from data.

• LIONsolver–>integrated software for data mining, business intelligence, analytics, and modeling Learning and also Intelligent Optimization.

• Microsoft Azure Machine Learning–>Cloud-based predictive analytics and also publishing of APIs on the cloud.

• STATISTICA–> advanced analytics software package which provides data analysis, data management, statistics, data mining, also machine learning etc

• SAS Enterprise Miner–> software suite used to mine, alter, manage and retrieve data from a variety of sources also to perform statistical analysis on it.

• Neural Designer–> software tool to mine data also based on machine learning techniques

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