The K-nearest neighbor (KNN) is a supervised machine learning algorithm. KNN is used mostly to classify data points although it can perform regression as well. The K-Nearest Neighbors Algorithm classify new data points to a particular category based on its similarity with the other data points in that category. The KNN algorithms grab the freedom […]
K-Nearest Neighbors Algorithm Read More »
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 »
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
Machine Learning Interview Questions (Part- 3) Read More »
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
A Lighter Perspective to Density Functional Theory Read More »
As an experimental physicist, I am always curious on whether I can extract accurate information in a situation where I have an enormous amount of experimental data whereas I left with apparently no direct theoretical/conceptual knowledge on it. The world around us is described with well formulated physics-based models. We can predict the orbit of
Physics Trained Machine Learning Models Read More »
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
Nanofabrication of MRAM Read More »
If you have some raw data and want to convert in into meaningful insight, feature engineering in machine learning is one of the best tools to help you. Imagine a real-life situation where you want to know how frequently a customer order food from your restaurant in order to offer best customer service. In such
Feature Engineering in Machine Learning Read More »
Supercomputers are a class of high-performance systems comprised of multiple central processing units (CPUs) in order to achieve high computational rates. They achieve fastest performance at a given time by using vector arithmetic which enables the system to operate on pairs of lists of numbers instead of simple pairs of numbers. For instance, if we
Quantum computing in supercomputers Read More »
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
Binomial Distribution Read More »
Frequentist and Bayesian are two schools of thought in probability theory. Let us look at the difference between them. Bayesian and frequentist approaches are two major frameworks in statistics for analyzing data and making statistical inference. The frequentist approach is based on the idea of probability as the long-term frequency of an event in repeated
Frequentist and Bayesian: A Quick Comparison Note Read More »