Call for Participation

Data science has become ubiquitous in modern society. A staggering amount of data is being generated and stored each day all over the world. This data is mostly related to social media, travel, communication, transactions, treatment, education, etc. The size and number of this “big” data have been increasing exponentially and will continue to grow at an accelerating rate for the foreseeable future. On a macroscopic level, most of this generated data is unused and might be discarded after sometimes. Effective analysis of these huge collections of apparently insignificant data can be very beneficial for companies, governments, medical organizations, etc. Despite the advancements in the broad field of computer science, storing, managing, processing and mining this “big” data is still a significant challenge. Machine learning plays an important role when it comes to making this “big” data useful. It creates a platform which helps to extract, understand and learn the underlying structure of this data. Traditional machine learning methods are not suitable for handling big data, hence they need to be adapted or new methods need to be evolved to tackle this situation. All this needs to be done for the “value” that this “big” data holds. This value will have a significant impact on a wide range of domains including health care, research, web services, finance & business informatics, scientific computing, and many others.

The aim of this workshop is to gather experts in Data Science and Machine learning, and facilitate the participants to get both theoretical and hands-on experience on different aspects of this subject. The workshop will provide a forum for exchanging ideas and information on current research studies, challenges, system developments, and practical experiences in this emerging field of Data Science and Machine Learning.