INTERACTIVE AND VISUAL APPROACHES TO DATA MINING

October 30 – November 03, 2017

Indian Statistical Institute, 203, B. T. Road, Kolkata-700108

Overview:

Data mining provides practical approaches and tools that allow researchers to analyze and understand their data and to craft new hypothesis. An important part of data mining is data visualization. Visualizations of data and models help researchers to uncover hidden relations, and help data mining users and data owners to understand the patterns that can lead to new discoveries and support their decision making. When data visualization is considered in combination with machine learning, their integration can be turned intoa powerful data exploration tool. If properly implemented within interactive, data exploratory environment, integration of data visualization and machine learning can be used as a discovery vehicle for any data-rich environment. Wielded in the hands of a curious data owner or data explorer, such tools may turn users into data scientist regardless of their background.

The course will focus on data mining essentials and will show how to combine data visualizations and machine learning into a powerful framework for data exploration. The course will cover standard approaches to clustering, classification, regression and model selection, image and text mining, but emphasize their relatedness to data visualization and techiniques that can help us in understanding of derived predictive models. The course will be hands-on and hence will be extremely useful, in particular for research scholars and practitioners from industry and R&D laboratories. We will focus on applications of these methods through a visual programming that, as presented through lessons of this course, will require no special training in programming. While the course will provide an introduction to inner workings and mathematics, we will focus on helping students to intuitively understand the data analysis algorithms through data and model visualization.  

Who should attend :

• Executives, engineers and researchers from industry and Government organizations including R&D laboratories.
• Student at levels (M.Sc./M.Tech./Ph.D.) or Faculty from academic Institutions.