In variable centered analysis, the focus is on the “average” learning pattern that ignores the unobserved heterogeneity between learners which makes it inadequate, whereas person-based methods account for heterogeneity and individual differences. Through this work, our aim is to identify sub-groups of people based on a set of variables such as abilities, motivation, preferences, etc, and understand inter-individual differences instead of bringing everyone in the same pool.
Research on what features impact and influence the pricing of cryptocurrency. Is it impacted by social trends, political influence, crude oils, etc. Impact of whales on the market and other attributes. Based on this information, I am trying to build a model for forecasting of cryptocurrency.
I am currently working on synthesizing music using supervised and unsupervised learning methodologies. I have collaborated with Karjan Institute, Austria and Vector Institute, Canada to work on this problem statement.