kishankumarthakur Goto Github PK

-google-play-store-analysis

-moveinsync

advanced-algorithms-and-complexity

Flows in Networks. Linear Programming. NP-complete Problems. Streaming Algorithms.

algo-on-graphs

Algorithms in Graph Theory written in Java, C++, and Python

algorithmic-toolbox-san-diego

✔ My Solutions of (Algorithmic-Toolbox ) Assignments from Coursera ( University of California San Diego ) With "Go In Depth" Part Which Contains More Details With Each of The Course Topics

algorithms-on-strings

Contains my code submission for Algorithms on Strings course as offered by University of California, San Diego & National Research University Higher School of Economics on Coursera.

applied-machine-learning-in-python

Solutions to the 'Applied Machine Learning In Python' Coursera course exercises

applied-machine-learning-in-python-1

applied-plotting-charting-and-data-representation-in-python

University of Michigan on Coursera

applied-social-network-analysis-in-python-course-work-quizzes-and-assignments-

applied-text-mining-in-python

University of Michigan on Coursera

applied-text-mining-in-python-1

This repository contains graded assignments in python-3 language of the course 'Applied text mining in Python', part of the specialisation 'Applied data Science using Python' by University of Michigan offered by Coursera.

applied-text-mining-in-python-2

Applied Data Science with Python Specialization: Course 4 (University of Michigan)

applied-text-mining-in-python-3

Repo for Applied Text Mining in Python (coursera) by University of Michigan

coursera-advanced-algorithms-and-complexity

This course talks about networks flows which are used in more obvious applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. It then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements, call routing in telecommunications and many others. Next discussing inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice.

coursera-alex

coursera-algorithmic-toolbox

This repository contains all the solutions for the assignments of the course - Algorithmic Toolbox offered on Coursera.

coursera-algorithms-on-strings

This course covers suffix trees, suffix arrays, and other brilliant algorithmic ideas that help doctors to find differences between genomes and power lighting fast internet searches.

coursera-applied-machine-learning-with-python

This repository includes course assignments of applied machine learning with python on coursera by university of michigan.

coursera-university-of-washington

University of Washington

coursera_2018_data_structures_and_algorithms

Coursera 2018/ data structures and algorithms / 6 course specialization by University of California, San Diego & National Research University Higher School of Economics

data-science-capstone

datagrokr

datasciencecoursera

Data Science

datasciencecoursera-1

for the peer grading

datastructures

design-a-scheduling-program-to-implements-a-queue-with-two-levels-level-1-fixed-priority-preempti

For a Fixed priority preemptive Scheduling (Queue 1), the Priority 0 is highest priority. If one process P1 is scheduled and running, another process P2 with higher priority comes. The New process (high priority) process P2 preempts currently running process P1 and process P1 will go to second level queue. Time for which process will strictly execute must be considered in the multiples of 2.. All the processes in second level queue will complete their execution according to round robin scheduling. Consider: 1. Queue 2 will be processed after Queue 1 becomes empty. 2. Priority of Queue 2 has lower priority than in Queue 1.

fundamentals-of-scalable-data-science

This repository has the solution to assignments for the course Fundamentals-of-Scalable-Data-Science by IBM on Coursera for future reference. It was a great learning experience and I would not want any other learners to take reference from the same and do them on their own.

genome-assembly-programming-challenge

Genome Assembly, de Bruijn Graph, Overlap Graph, Bubbles and Tips Removal, Optimal K-mer, Phi X174 Genome, Error-Prone Reads, Universal Circular String, Eulerian Cycle.

intro-to-data-science-in-python

Repo for the first course of the Applied Data Science with Python Specialization taught by University of Michigan hosted by Coursera