Pinned Repositories
Angular-2-Gridster-D3
Data-Mining
Performed Time Series Data Trend prediction using ARIMA model
European-Bank-ID-authentication
Swedish Open Bank Id Authentication in Angular & Node Js
react-pwa
Firebase Hosted PWA using react which follows all the characteristics of ideal PWA like service worker, caching
tsPrediction
Time series prediction system in R (RStudio) for given real-time e-commerce dataset of thousands of products, customers, and categories with the help of data mining algorithms (ARIMA, Holt Winter, STL, ETS).
wavesurfer-audio-editor
Wavesurfer audio editor with basic functinalities like cut, copy, paste
vikasmagar512's Repositories
vikasmagar512/react-pwa
Firebase Hosted PWA using react which follows all the characteristics of ideal PWA like service worker, caching
vikasmagar512/Angular-2-Gridster-D3
vikasmagar512/European-Bank-ID-authentication
Swedish Open Bank Id Authentication in Angular & Node Js
vikasmagar512/Algorithms-by-S.Dasgupta
Attempts to solve exercises and implementation of algorithms from Algorithms by S.Dasgupta et al.
vikasmagar512/almabase-assignment
Admin Panel
vikasmagar512/angular-2-dialogBox
DialogBox using Angular-2
vikasmagar512/CasinoReactTruffleDAPP
vikasmagar512/JavascriptPWA
Simple Javascript PWA
vikasmagar512/mernSFS
vikasmagar512/Mindsphere
Test av Mindsphere
vikasmagar512/mindsphere-hackathon-201805
vikasmagar512/mindsphere-node-hello-world
vikasmagar512/onePasswordLayitechHrUpwork
vikasmagar512/Operating-Systems-CS550
My Classwork solutions for Operating Systems (CS550) - Spring 2017
vikasmagar512/Pinnakl
vikasmagar512/Place-order
Make a solution in PHP that solves the following problem. A company sells hundreds of products on-line and people place orders from all over the world, just like eBay. Each item has a different weight and price. And each order can be a combination of different number of items. Now each of these orders are to be put into different packages and sent to the courier company for delivery. But there are certain rules while splitting items into packages, they are as below: 1. If the cost of all the items in an order is more than $250, split those items into multiple packages, otherwise one package would be enough. 2. If the items in the same order are split into multiple packages, then the weight of the packages should be equally distributed over the packages to save courier charges. 3. While splitting, NO PACKAGE can have a total price above $250 Create a page (You may want to use JQuery/Angular, HTML5, bootstrap) which has the following: 1. A simple vertical list of items (in the format Name - price - weight), with a check box next to item 2. A button saying "Place order" When the user clicks on "Place order", the selected items should be submitted to the same page without refreshing the page and the above splitting rules should be applied to divide this particular order into multiple packages, and display the output result on the same page.
vikasmagar512/project_redux_LaitechHR_Upwork
vikasmagar512/projecto
vikasmagar512/push-notifications
vikasmagar512/React-Redux-Thunk-Middleware-Authentication-System
React Redux Authentication System
vikasmagar512/React-Stomp-SparkLine-Websocket
vikasmagar512/reactSocialMedia
vikasmagar512/restaurant-finder-geolocation
restaurant-finder-geolocation
vikasmagar512/Sales-Data-Prediction-system
The specific problem in this project is about the time-series data trend prediction. The specific application scenario is in e-commerce. You are given a real dataset obtained from a real-world e-commerce application where there were 1000 products and 31490 customers (i.e., buyers) who bought these products. Of these 1000 products there are 100 key products (popular products). Also these 1000 products are in 15 categories. The specific data are given in the seven tables and the specific details of these tables are given below. The time window of this dataset is in 118 days with data documentation for each day. Hence, the time unit is one day where the timeline goes from the 0-th day to the 117-th day (17 weeks less one day in total). Now you are asked to do the sale quantity prediction for the 100 key products for each day between the 118-th day and the 146-th day (29 days).
vikasmagar512/ShimmerRecyclerView
Explains how to implement Shimmer in Recycler view & shared Element Transition
vikasmagar512/Signing-verifyingWeb3Solidity
vikasmagar512/SocialMedia
Social Media using NodeJs, Hapi.js, MongoDb
vikasmagar512/Trakt-Movie-Explorer
IMDB Movie explorer
vikasmagar512/Uport-React-Truffle-Box
vikasmagar512/webpack-express-node-react