Ensemble methods made easy – Bagging, Boosting, Stacking, Averaging and Voting.

Loveesh is Data & Decision Science professional with wide domain experience and skill set. He’s proficient in programming languages like Python, R, SAS, VBA and query languages such as Hive and SQL. Loveesh mainly works with machine learning algorithms such as XGBoost, GBM, adaboost, random forests and regressions both logistic and linear. He also has solid expertise in optimization techniques such as grid search, regularization and gradient descent.

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