Anirudh181001/Web-Dev-With-Flask

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Python
Created almost 2 years ago
Updated almost 2 years ago

Anirudh181001/Web-Dev-With-Flask

Anirudh181001

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Hill-Estimation-of-Social-Datasets

The Hill estimator is often used to infer the power behavior in tails of experimental distribution functions. Hill's tail estimator enables us to predict the tail index using certain parameters. During my undergraduate research oppurtunity with a professor in SUTD, I had written codes in R to estimate tail index using Hill Estimators for different types of datasets.

Schrodinger-s-Equation

I had coded out the Schrodinger's equation in order to help visualize and understand the orbitals in an atom as part of my undergraduate study in SUTD. A bit of starter code was provided by professors in order to facilitate feasibility of this project.

Metropolis-Hastings

As part of the simulation of Restricted Boltzman Machines, I had coded out the Monte Carlo Markov Chain Metropolis Hastings algorithm in order to generate a suitable list of electronic configuration to work with for the rest of the RBM. This was done as part of my Physics Honours Course during my undergraduate in SUTD.

Conditional-Random-Sampling

Conditional Random Sampling (CRS), a technique particularly suitable for sparse data. In large-scale applications, the data are often highly sparse. CRS combines sketching and sampling in that it converts sketches of the data into conditional random samples online in the estimation stage, with the sample size determined retrospectively.Conditional Random Sampling (CRS) is a sketch-based sampling technique that effectively exploits data sparsity. In modern applications in learning, data mining, and information retrieval, the datasets are often very large and also highly sparse. The following codes were written in MATLAB in order to simulate the CRS algorithm in the honours maths course taken during my undergraduate study in SUTD.