Data Analyst And Server Admin
Areas of Expertise: Simple Linear Regression, Mutiple linear regression, Logistic regression, KNN Algorithm, KMeans clustering, Hierarchical clustring, Decision tree, Random Forest, Dimensionality reduction technique PCA, Sklearn library, seaborn plots, numpy, pandas dataframes, sound Knowledge on Python and Azure. Project: Problem Statement : To identify user behaviour patterns and determine the likelihood of purchase based on the given features for online purchase consumer data. Objective : Create all machine learning models and choose the most optimum model and their respective feature importance that influence the sales of the client data . Outcome: The approach consists of understanding the data by Exploratory Data Analysis, feature engineering, feature selection, model building, model validation, hyper parameter tuning and ensemble different models.Tools Used : Python, sklearn libraries
