rohitraj15 Goto Github PK

carwash.com

dimensions-of-shapes

This is a MENU-DRIVEN python programme which calculates and prints the basic information of 2D or 3D shapes like perimeter, area, curved surface area etc.____Input-: The programme will ask you to select a shape as per displayed in the menu, and then you are requested to input given the respective parameters of that shape(including floating point numbers)._____Outputs-:It will print the basic geometry of the shapes like area, perimeter, etc as mentioned earlier.

flipzon

FLIPZON - A prototype of a standard e-commerce website in Java

laundary-service

This is a python code for the Laundry Service center, which has to calculate the total charge and tell the user how many days they will get their clothes with a customer ID.____Inputs:___Name of customer[string]____Contact of customer [integer]___Email Alphanumeric [string]___Type of cloth “Cotton,” “Silk,” “Woolen” or “Polyester”[string]___Branded “0” for unbranded, “1” for branded [Boolean]__ Season “Summer” or “Winter” [string]___It calculates the charges on the following factors:__1.Type of cloth: Cotton → 50 Rs, Silk → 30 Rs, Woolen → 90 Rs, Polyester → 20 Rs.__ 2. Branded: if True, 1.5 times the charge from step 1. Otherwise, the charge is unchanged___ 3. Season: if it is “Winter,” the charge is halved from step 2. Otherwise, the charge is two times the charge from step 2.___Outputs:___It will print the customer details and tell the expected day of return on the following factors:___1. If the total charge is greater than 200, it will print out “To be returned in 4 days.”___ 2. Otherwise, it will print out “To be returned in 7 days.”

movie-recommended-system

This Movie Recommendation System uses machine learning to enhance the movie-watching experience. It analyzes user preferences, movie metadata, and historical data to suggest personalized movie recommendations, tailored to individual tastes.

my-flex

my-portfolio

my_resume

tindog-tinder-for-dogs-

whether-prediction

This project predicts tomorrow's temperature using historical weather data. We download a dataset, customize it for our location, clean the data, and prepare it for machine learning. We build a system for historical predictions and enhance the model by adding more predictors. Finally, we learn how to make accurate next-day temperature predictions.