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Articles by Subhasis Sanyal
A Comprehensive Guide on Markov Chain
This article was published as a part of the Data Science Blogathon. Overview · Markovian Assumption states that the past doesn’t give a piece of valuable information. Given the present, history is irrelevant to know what will happen in the future. · Markov Chain is a stochastic process that follows the Markovian Assumption. · Markov chain had given a new dimension to probability theory. The applicability can be seen almost in every field.
A Comprehensive Guide on Fourier Analysis
This article was published as a part of the Data Science Blogathon. Overview The importance of the Fourier analysis is paramount. It is one of the pillars of engineering, and we can say it is a study of “atoms of waves”. Pretty much anything you can imagine which has a spectral decomposition interpretation, from mechanical engineering to deep-space communications to pre/postnatal healthcare to modern optics, Fourier analysis has its omnipresence. So, Let’s demystify Fourier analysis over here.
An Introduction to Particle Swarm Optimization (PSO) Algorithm
PSO is a stochastic optimization technique based on the movement and intelligence of swarms. In PSO, the concept of social interaction is used for solving a problem. It uses a number of particles (agents) that constitute a swarm moving around in the search space, looking for the best solution. Each particle in the swarm looks for its positional coordinates in the solution space, which are associated with the best solution that has been achieved so far by that particle.
An Intuition about Kalman Filter
This article was published as a part of the Data Science Blogathon Overview The importance of the Kalman filter relies on removing the noise from input data. It is one of the great tools to have during the data capturing process. It is based on a linear dynamical system, which is based on the Continuous Markov Chain model. The applicability of the Kalman filter is very vast. Particular use can be seen with sensor-based systems.
RAKE Algorithm in Natural Language Processing
Overview 1. Rapid Automatic Keyword Extraction(RAKE) is a Domain-Independent keyword extraction algorithm in Natural Language Processing. 2. It is an Individual document-oriented dynamic Information retrieval method. 3. Concept of RAKE is built on three matrices Word Degree (deg(w)), Word Frequency (freq(w)), Ratio of the degree to frequency (deg(w)/freq(w)). Introduction In the field of Machine Learning, thanks to ‘No Free Lunch” (NFL), we have multiple options of algorithms to solve a problem.
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