Vikas Magar's repositories
European-Bank-ID-authentication
Swedish Open Bank Id Authentication in Angular & Node Js
Algorithms-by-S.Dasgupta
Attempts to solve exercises and implementation of algorithms from Algorithms by S.Dasgupta et al.
almabase-assignment
Admin Panel
angular-2-dialogBox
DialogBox using Angular-2
JavascriptPWA
Simple Javascript PWA
Mindsphere
Test av Mindsphere
Operating-Systems-CS550
My Classwork solutions for Operating Systems (CS550) - Spring 2017
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.
React-Redux-Thunk-Middleware-Authentication-System
React Redux Authentication System
restaurant-finder-geolocation
restaurant-finder-geolocation
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).
ShimmerRecyclerView
Explains how to implement Shimmer in Recycler view & shared Element Transition
SocialMedia
Social Media using NodeJs, Hapi.js, MongoDb
Trakt-Movie-Explorer
IMDB Movie explorer