nishantk2106/sqllite_workings

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nishantk2106/sqllite_workings

nishantk2106

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sql queries

R_workings

workings on R assignments

travello_app

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

sparkstreamingexample_workings

sas_workings

working on SAS academics program

scala-spark_workings

network-programs

network program using url in python

python_more-learning

python-

my python learning

python_workings

my python learning

postgresql_workings

Spatial database

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

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

Blog_app

Creating a blog app using the Django framework

flightreservation-system

flight reservation system using the django_rest framework

shorturl

creating shorturl using django_restframework