Kavya Parashar

Background

About Kavya Parashar

A Data Science enthusiast with extensive data engineering experience. So far gained knowledge in Machine Learning and Deep Learning in Python and R: • Supervised Learning Methods: Regression Techniques, Classification Methods, Decision Trees, SVM • Unsupervised Learning Methods: K-Means Clustering • Ensemble Techniques: Random Forest, Bagging, Gradient Boosting, AdaBoost, XGBoost • Fine-tune (GridCV, RandomCV) • Artificial Neural Networks and Convolutional Neural Networks • Time Series Forecasting: Auto-regression (AR), Moving Average (MA), ARMA, ARIMA, SARIMA, SARIMAX. Big Data Handling in Hadoop Database Concepts in • SQL • NoSQL- MongoDB, HBase, Gremlin Statistical Programming in R • Descriptive • Inferential Data Visualization and Business Insights in • Tableau • PowerBI Looking forward to make an impact, analyzing data.