• Proficiency in different categories of machine learning techniques such as regression, classification, kNN, decision trees, dimensionality reduction, and clustering.
• Application of different performance metrics, and selection of performing model.

• Application of Bayesian and Mixture models and Bayesian inference algorithms
• Perform text mining and information retrieval

• Proficiency in building deep learning models for both visual and text/ sequence processing problems and generative models
• Develop deep reinforcement models for automation

Conceptualisation, design, development and evaluation of Artificial Intelligent model with a classic or deep machine learning framework