IIMA PGP’26 | Microsoft | Ex-Frontend Dev

leetcode

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Arju Aman  • Peerlist

Uniform-cost search is a searching algorithm used for traversing a weighted tree or graph. This algorithm comes into play when a different cost is available for each edge. The primary goal of the uniform-cost search is to find a path to the goal node which has the lowest cumulative cost. Uniform-cost search expands nodes according to their path costs form the root node. It can be used to solve any graph/tree where the optimal cost is in demand. 
in 8-puzzle problem, it consists of an area divided into a grid, 3 by 3 for the 8-puzzle. On each grid square is a tile, expect for one square which remains empty. Thus, there are eight tiles in the 8-puzzle. A tile that is next to the empty grid square can be moved into the empty space, leaving its previous position empty in turn. Tiles are numbered, 1 to 8 for the 8-puzzle, so that each tile can be uniquely identified. Aim of the puzzle is to achieve a given configuration of tiles from a given (different) configuration by sliding the individual tiles around the grid.


8 Puzzle Problem using Uniform Cost Search

It was done using PYTHON Programming Language using the required libraries.
The wavelet transform has emerged over recent years as a powerful time– frequency analysis and signal coding tool favoured for the interrogation of complex non stationary signals. Its application to bio signal processing has been at the forefront of these developments where it has been found
particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG was discussed in detail.

ECG Compression Using Wavelet Transform

I worked on the data from: https://www.tdcj.texas.gov/death_row/dr_executed_offenders.html 
My aim was to get a list of all the last statements by those who were executed and then make a WordCloud visualization of the most often words by them, conditions being that length of words should be greater than 5. I started with spidering the data from the site, used BeautifulSoup for the anchor tags,and then again for the consequent paragraph tags, put them into a list and consequently wrote into a file. I imported that file in a datagram, cleaned it and exported it to csv, which helped me in converting to sqlite. Then I created a python file to get the visualization.

Last Words at Deathbed (Case study): Pagerank, Spidering, Sc

Tools used: Python, Flask, HTML
This project describes patient medical record data for Pima Indians and predicts using a sequential model whether they had an onset of diabetes within five years. The aim is to build a model robust enough such that if we feed in more data in the future, it could prove beneficial to the medical world.