Profiling and Analysis Platform Using Deep Learning
The data, regardless which media been sourced from, have critical importance to any industry as well as for the quality of life. It enables unlocking power of Text, Big Data and Deep Learning by paving the way to do highly efficient analytics such as sentiment analytics, trend analysis, radicalization detection, the list goes on. The scope of the project is to build a universal model for data analytics that is executed on a proposed set of technologies that fit best to the data provided. Indeed, before applying any kind of algorithm such as text summarization, translation or semantic analysis, we need to build and learn the representative model for data. As per this model creation process, several complexity dimensions must be taken into account (e.g. language, structure, semantic, etc). Businesses currently deal with a data set more than they can handle. Today's necessity is not the usage of data analytics, it is the utilization of combined technologies in which data analytics are executed to make sense out of the data. Business relevance of this project would be realized on the domain specific analysis of structured or unstructured data considering dynamics of the applied industry complied with the expected outcome to the optimal extent in any domain. That being said, project would best fit to the data concentrated domains such as media, finance, government in which project outcome will be honored to serve stakeholders of these domains in servicing their clients by profiling them and matching their profile to the provided services. The key focus of this project is to build an application-agnostic analytical platform for data analytics that enables exploiting data to suggest an efficient model that performs powerful analytics with high precision and accuracy and discovers actionable insights.