Hollow out the insights of Data for Decision 

The data intelligence has consistently expanding computational methods without limits. Artificial intelligence powered by machine learning and deep learning has gone through some extraordinary changes over the last era. Preliminary, pure academic and research-oriented domain, have widespread industry acceptance across diverse domains including retail, technology, healthcare, science and many more. Hence, in the industry, the main focus of data science or machine learning is more ‘applied’ rather than theoretical and effective application of these models on the right data to solve complex real-world problems is of paramount importance. More than often, the standard toolbox of machine learning, statistical or deep learning models remain the same. The workshop covers the data pipeline, cross industry standard process for data mining methodology that provides anyone from novices to experts to complete blueprint for conducting a data mining project. 




The purpose of this workshop is to introduce attendees to the capabilities and features of Data analytical tools, and to provide guidance on how they can use ML studio, R-Scripts, SQL- Transformations in their own applications to start taking advantage of the data visualization over the dataset. 

Target Audience

Open to research students, scientists, engineers and anyone who wants the speed of machine learning techniques in-data analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately and make decisions based on what they have learned.

Relevance to ICO2020

There are increasing numbers of researchers in the area of visual data analysis technologies,
and these users will be interested in learning about the features and capabilities in ML Studio,
R-Graphics, data visualization that include:

  • Free, open Machine Learning Studio

  • R-run time, Open(MRO)3.4.4

  • Machine Learning Transformations

  • Geometrical Objects and Aesthetics

  • Packages for data visualization

  • What is CRISP-DM?

    • Business Understanding

    • Data preparation

    • Modelling, Evaluation, Deployment

  • Learning Data with ML Studio

    • Sensor Data

    • Data Pipeline-Integration

    • Run and Execute

  • Analyze the Data Science Techniques

    • Regression, data visualization

    • R-Graphics, plots with ML

    • Run ML Algorithms.

Educational Objectives

At the end of this workshop, attendees will have gained knowledge and experience on:

  • ML studio exploration – functionalities and features

  • Data-decision processing and specialized algorithms for dealing with data that arrives so fast it must be processed immediately or lost.

  • Algorithms for clustering very large, multivariate dataset.

Speakers and Instructors

The speaker for this tutorial will be:

  • J. Joshua Thomas Ph.D., Senior Lecturer Department of Computing, UOW Malaysia, KDU Penang University College.

  • Pandian Vasant Ph.D., School of Applied Sciences, University Technology Petronas, Malaysia.

Presentations (tentative)
  • Overview of Data-Platform (30 min) Pandian Vasant

  • Installation of resources for hands-on exercises – Part 1 (60 minutes) J. Joshua Thomas

  • Break (15 min)

  • Hands-on exercises –Part 2 (60 minutes) J. Joshua Thomas

  • Summary (10 Minutes)


This is a hands-on workshop for data analytics with ML-Studio. The workshop is conducted in the Lab with PCs already installed with the latest version of R-Studio. Attendees may bring their own laptops to the workshop and able to have Microsoft email account prior to the day of the workshop. At the beginning of the workshop, attendees will receive USB memory sticks, containing the build of R-Studio along with a collection of exercises to be run during the workshop.

About the Speaker

  • J. Joshua Thomas, Ph.D., is currently a senior lecturer in department of computing at the School of Engineering, Computing and Built Environment, UOW Malaysia; KDU Penang University College. He received his PhD in Intelligent Systems from University Sains Malaysia. His work is involved with optimization, visual representation of the process, computational steering through visual cues and tune algorithmic parameters while the process runs. His current focus is on Deep Learning, Data Analytics, Big-Data, Visual Analytics and its applications. He was the recipient of Best Paper Award in IEEE- CS Malaysia at the Visual informatics (IVIC2017). He gave plenary talk at the International conference on Artificial Intelligence and Maching learning (IAIM2019). He was a workshop presenter in IVIC2019. Recently he has edited a book on Deep Learning Techniques and Optimization Strategies in Big Data Analytics. He is an editorial board member for the Journal of Energy Optimization and Engineering (IJEOE), and invited guest editor for Journal of Visual Languages Communication (JVLC-Elsevier). He has published more than 30 papers in leading international conference proceedings and peer reviewed journals and guest editor of Special Issue "Applied Optimization in Clean and Renewable Energy: New Trends" MDPI publishers.

  • Dr. Pandian Vasant is an Editor-in-Chief of IJEOE (ESCI/WoS). He holds PhD in Computational Intelligence (UNEM, Costa Rica), MSc (UMS, Malaysia, Engineering Mathematics) and BSc (Hons) in Mathematics (MU, Malaysia). His research interests include Soft Computing, Hybrid Optimization, Innovative Computing and Applications. He has co-authored research articles in journals, conference proceedings, presentation, special issues guest editor, book chapters (257 publications indexed in Web of Science). In the year 2009 and 2015, Dr. Pandian Vasant was awarded top reviewer and outstanding reviewer for the journal Applied Soft Computing (Elsevier). He has 26 years of working experiences at the universities. Currently he is Editor-in-Chief of International Journal of Energy Optimization & Engineering, and Member of AMS (USA), NAVY Research Group (TUO, Czech Republic) and MERLIN Research Group (TDTU, Vietnam).