It is often required for aspiring data scientists to do portfolio projects either to show their skills or just simply for the pure joy of doing it. In either cases, the complexity of the project can be often a small one to medium one. To truly convince the recruiters, it is often required to do …
What are Support Vector Machines? Support Vector Machines (SVM) is one of the most elegant methods used for classification and regression in machine learning (ML). We can use SVM when we have a bunch of objects/features which we want to classify. SVM performs the classification by drawing a hyperplane (Figure.1) to separate each category of …
This post is a case study on primary or metastasis classifier using deep learning models. Overview Genetics is behind every physiological aspect of a living being such as height, eye color, hair color, etc. Mutations are unwanted changes happening to genetic code for various reasons. The main reasons account for such changes are hereditary, exposure …
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This tutorial walks you through building a breast cancer survivability prediction classifier which use clinical and gene expression data by employing machine learning techniques. Overview Cancer is a disease in which cells in the human body grow uncontrollably. This phenomenon often spreads to other parts of the body. Human bodies contain trillions of cells. Human …
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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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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 …
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 …
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 …
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 …
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 …