Summary of the book “The Five Elements of Effective Thinking”

In this blog post, I am going to summarize the key ideas from the book titled “The Five Elements of Effective Thinking” written by Edward Burger and Michael Starbird along with my thoughts on the topic. The preface starts with arguing that thinking is the skill which forms all other skills like decision making, creativity, …

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Machine Learning Interview Questions (Part- 2)

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 classification tasks involve more than one type of classes in the data set or the classification problem contains an …

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Machine Learning Interview Questions (Part- 1)

Explain the terms Artificial Intelligence, Machine Learning, Deep Learning, and Reinforcement Learning? Artificial Intelligence (AI) is the domain of intelligent machines which can think rationally and act rationally. It uses algorithms to enable problem solving with robust dataset. Machine Learning (ML) and Deep Learning (DL) are subfields of artificial intelligence in which deep learning can …

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Writing Python Wrapper for Bioinformatics Tools

The use of computational tools for data preprocessing and analysis is daily activity for any bioinformatician. Having a interdisciplinary field, a plethora of tools exist in the domain, written by developers from various fields and languages. Many times there can be multiple candidate tools exists to accomplish any given task. Often it is the decision …

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Molecular Docking in Google Colab

Molecular docking is an essential process in scientific drug discovery. By using the recent advances in generative deep learning the runtime required for such docking studies can be reduced significantly without comprimising accuracy compared to traditional methods. In this article, let us get familiarize ourselves with one open-source molecular docking codebase. The codebase named DiffDock …

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svm hyperplane

Essential Concepts and Implementation of Support Vector Machines

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 …

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Predicting Genetic Mutations as Primary or Metastasis Using Deep Learning

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 to environmental radiation, and errors that occur in DNA replication. Some of these mutations alter …

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Breast Cancer Survival Prediction with Clinical and Gene Expression Data

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 growth starts with a one-celled zygote. Both sperm and egg from biological parents meet and form the zygote. The process of cell division is …

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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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