More than two years of experience in Machine Learning with Python using Jupyter Notebook. Sound exposure to Data Preprocessing, Data Analysis techniques like Data Visualization, Feature Engineering, and Statistical Analysis; and model designing with Machine and Deep Learning algorithms.
Analyzed different industries dataset for designing algorithms related to predictive modeling and clustering but not limited to automotive, banking, education, energy, housing, medical, retail, sports, telecom, and trading.
Besides, replicate a journal paper ( Beijing Housing Price Prediction via Improved ML Techniques) for estimating London residential prices for one of the client master thesis involving geospatial data, transaction data, and macroeconomic data.
Also worked with the FiFA19 player dataset and tried to make analysis like "can we predict correctly Potential or Ball Control of a player on the basis of other features or player skills, a regression analysis. Also visualizing wages against each club. The FIFA19 dataset gives you complete information about the players who are involved in club football or international. The information consists of Age, Wage, Country, Club, and skills.
Playing Fantasy Barclays Premieir League these days too.