Logistic Regression for Classification in Machine Learning

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 …

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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- 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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Density Functional Theory

A Lighter Perspective to Density Functional Theory

The diverse properties of materials upon which material science researchers possess enormous enthusiasm are categorized into magnetic, transport, optical and superconducting properties. As we know, materials are made up of atoms comprised of electrons and nuclei and all these material properties originate from the interactions among electrons and atomic nuclei. Classical mechanics can describe the …

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Nanofabrication of MRAM

Nanofabrication deals with the fabrication of materials and structures at nanoscale. The essential requirements of a nanofabrication are a clean room which is devoid of particles and contaminations and also a specially designed equipment facility for thin film deposition, patterning and etching. We are all familiar with integrated chips (ICs). ICs are manufactured through nanofabrication …

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Binomial Distribution

Introduction Probability distributions are cornerstones in the theory of machine learning. The entire field of machine learning is often theoretically viewed or explained from a probabilistic perspective. Compared to the linear algebraic point of view, the probabilistic perspective gives formulations of machine learning algorithms that are more impressive. Binomial distribution is one of the many …

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