Deliberating on machine learning and data science
S Vishnu Sharmaa, INN/Chennai, @Svs03
Mahindra Ecole Centrale College of Engineering (MEC) was the centre of attraction recently when the third international conference on machine learning and data science was held. It deliberated in depth about algotithms, systems, applied and research aspects of machine learning and data science.
The two-day conference ICMLDS-2019 (16 and 17 December) focused on topics that are of interest to computer and computational scientists and engineers. The conference featured eminent speakers and presentations of peer reviewed original research papers and exhibits.
Navin Mittal, Commissioner, Collegiate Education and Technical Education, Government of Telangana inaugurated the conference. Navin Mittal focused on the coming together of a truly international community for the conference.
He reiterated that the whole field is getting increasingly integrated in our lives. Giving examples from the Technical Education Departments, he said that the answer scripts of students are being run through an AI engine as a pilot and digitized the complete process.
He also stated that in Government of India’s Smart Cities Project, increased use of machine learning and data integration is helping us avoid wastage and is instrumental in keeping us safe.
Dr. Yajulu Medury, Director, MEC said they are proud to be hosting the third edition of the conference, some of the biggest names in the industry have partnered with the conference.
Machine learning, big data and data sciences are so much a part of our lives today that we barely even notice them or realize the breakthrough scientific research that made them possible.
‘We at MEC are committed to partnering research in the segment and have set up a specialized Artificial Intelligence and Machine Learning Research Centre on campus.’
Professor Prafulla Kalapatapu from the Computer Science department at MEC and Professor Sartaj Sahni, distinguished professor of Computer Science, University of Florida, were the General Co-chairs of the conference.
Various topics of focus in Machine Learning included Model Selection, Evolutionary Parameter Estimation, Graphs and Social networks, Non-parametric Model for Sparse Networks, Large Scale Machine Learning, Learning Paradigms, Deep Learning, Recommender Systems, Applications and Evaluation of Learning Systems.
In Data Science, the focus was on all aspects including Algorithms, Novel Theoretical and Computational Models, Data and Information Quality, Data Integration and Fusion, Data Acquisition, Integration, Cleaning, Mining, Data Wrangling, Data Cleaning, Data Curation, Data Munching, Data Analysis, Statistical Insights and Decision Making, Data Science technologies, tools, frameworks, platforms and APIs and Applications.
