Nishant Kumar (@nishantk2106)
github

nishantk2106

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  • Stars
    star
    44
  • Global Rank 373,242 (Top 13 %)
  • Followers 4
  • Following 2
  • Registered about 5 years ago
  • Most used languages
    Python
         46.7 %
    Jupyter Notebook
         13.3 %
    Scala
         13.3 %
    HTML
         6.7 %
    SAS     6.7 %
    CSS
         6.7 %
    PLpgSQL     6.7 %
  • Location <UNKNOWN>
  • Country Total Rank 1,128

Top repositories

1

R_workings

workings on R assignments
HTML
3
star
2

travello_app

A prototype of travel booking app for different location in india using Django framework and postgresql as the database
CSS
3
star
3

sparkstreamingexample_workings

Scala
3
star
4

sas_workings

working on SAS academics program
SAS
3
star
5

scala-spark_workings

Scala
3
star
6

network-programs

network program using url in python
Python
3
star
7

sqllite_workings

sql queries
3
star
8

python_more-learning

python codes
Python
3
star
9

python-

my python learning
Python
3
star
10

python_workings

my python learning
Python
3
star
11

postgresql_workings

Spatial database
PLpgSQL
3
star
12

House_price_data

A cross-validated k-nearest neighbour model from the house price data, and produces the following: A 3-D plot of the house price for average floor area. A 3-D plot of the house price for floor areas of 75 square metres. A 3-D plot of the house price for floor areas of 125 square meters.
Jupyter Notebook
3
star
13

GoogleSvrLog_dataset_python

Resource utilization is one of the key performance indicators for measuring the operational efficiency of cloud datacentres. Current cloud datacentres employ sophisticated task scheduling algorithms to improve resource utilization. The analysis of the algorithms is primarily based on analytical approaches. Due to the dynamicity and heterogeneity of cloud datacentre environment, the actual performance of the scheduling algorithms is often far beyond from the analytical results. Thus, it is important for researchers to be able to replay the historical operations on task placement and to offer a global view on the status of the cloud datacentre at any moment. In this project, we aim to provide a data-driven task placement replay simulation for cloud data centre, supported by big data technologies.
Jupyter Notebook
2
star
14

Blog_app

Creating a blog app using the Django framework
Python
1
star
15

flightreservation-system

flight reservation system using the django_rest framework
Python
1
star
16

shorturl

creating shorturl using django_restframework
Python
1
star