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.

Hyperparameters in Machine Learning

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 …

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Machine learning Interview Questions (Part-4)

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 …

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Machine Learning Interview Questions (Part- 3)

The article discusses interview questions asked in many machine learning job roles Explain label encoding and one hot encoding, Explain how the dimensionality of a dataset is affected with these methods in machine learning Machine learning algorithms can understand only numbers. Often, the dataset consists of categorical and numerical features. We need to convert the …

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Machine Learning Interview Questions (Part- 2)

This article is one among the series of discussions on interview questions frequently asked in machine learning job roles Explain the concept confusion matrix in machine learning? Confusion matrix is a table displaying a summary of prediction results of a classification problem. Measuring accuracy of a model alone can be misleading in cases where the …

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