Roshna S H

Dr. Roshna S H is a scientist by profession with more than five years of teaching experience at graduate and postgraduate levels. She has obtained a Ph.D. from IIT Madras after M.Sc., M. Phil in Physics. She has also cleared CSIR-NET and GATE with top ranks. She is a constant content creator through publications in peer-reviewed international journals and by writing concept based blog articles. She has research experiences in diverse areas spans from atmospheric science to optics as well as spintronics and magnetism. She has obtained awards and recognitions at various international platforms for her contributions as scientific articles and oral presentations. Dr. Roshna completed her Ph.D. with exposure at American physical society, Material research society, University of Oxford, etc. She focuses on communicating the concepts with utmost clarity in the simplest possible way.

Logistic Regression for Classification in Machine Learning

1 Comment / Conceptual, Tutorial / By

Logistic regression is an analytical technique in supervised machine learning for performing classification tasks. It is a classification algorithm based on probabilistic approach. Logistic regression approach can be used to make predictions on a categorical dependent variable. The algorithm extracts inferences from a given set of independent input variables and these inferences are used to …

Logistic Regression for Classification in Machine Learning Read More »

Computational Prediction of Electronegativity Difference with Radius in Perovskites

Leave a Comment / Case Study / By

Overview Materials science is a field of study that involves the research and discovery of new materials and its functional properties for applications in electronic storage devices, biomedical instrumentation, telecommunication equipment etc. The applications of material science spans from designing of products by exploiting its material properties to the manufacture of products which can contribute …

Computational Prediction of Electronegativity Difference with Radius in Perovskites Read More »

Machine learning Interview Questions (Part-6)

Leave a Comment / ML Interview Questions / By

This article discusses a couple of machine learning (ML) interview questions asked frequently in data science related job roles. When should we prefer ridge regression over lasso? Explain with reason Ridge regression is a regression in which we use L2 regularization to give a penalty to the loss function to reduce loss in the optimization …

Machine learning Interview Questions (Part-6) Read More »

Hyperparameters in Machine Learning

Leave a Comment / Conceptual / By

Introduction Hyperparameters are the parameters that are explicitly defined by the user for the machine learning model. This helps the learning process of the machine learning algorithm. The prefix “hyper” in hyperparameter means top-level, indicating these are the controlling parameters to ensure model performance. The user selects the value of the hyperparameter before the training …

Hyperparameters in Machine Learning Read More »

Machine learning Interview Questions (Part-4)

Leave a Comment / ML Interview Questions, Resource / By

This is one among the series of frequently asked interview questions in machine learning. Concepts are demonstrated with schematics wherever necessary Differentiate between local optimization and global optimization Optimization is a process of assigning a set of inputs to an objective function that can extract the best possible output from the objective function. Local optimization …

Machine learning Interview Questions (Part-4) Read More »