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saimedavarapu's Projects

angular icon angular

This repository consists of the files and notes for individual topics on Angular 7.

appointment-scheduling icon appointment-scheduling

Full stack application built using ASP.NET Core, EF Core, SSMS and Angular. This lets the user schedule an appointment and Perform CRUD on it.

asp.net-core-cities-web-api icon asp.net-core-cities-web-api

Web API for 'Things to do In Cities'. Cleint can perform CRUD operations through this API. This project exposes the Restful API end points for 'Things to do in Cities'. It is built using ASP.Net Core 2.0, EF Core and SQL Server

bankchurnprediction icon bankchurnprediction

This is the implementation of the churn issue in the banks which is implemented using the Artificial Neural Network

data-integration-using-api icon data-integration-using-api

I have developed the Data Integration web application using Jquery, Javascript, HTML and CSS by Integrating Weather underground, Zomato and Google maps API

diabetes-prediction icon diabetes-prediction

I have ran few machine learning algorithms to predict the diabetes using Python in Anaconda.

ecommerce-website icon ecommerce-website

Building a Web App with ASP.NET Core, MVC, Entity Framework Core, Bootstrap, and Angular

elevatorsimulationusingc- icon elevatorsimulationusingc-

Design and implement three different algorithms to simulate the elevator movement in order to response to the requests.

portfolio-website icon portfolio-website

This my portfolio website describing a little about me and a few projects which is developed using Angular

suzukikasamimpi icon suzukikasamimpi

The Suzuki-Kasami algorithm is a token-based algorithm for achieving mutual exclusion in distributed systems.

weatherforecast icon weatherforecast

Integration of Open weather API using Angular, Angular Material. It gives the Current Day weather details and 5 Day forecast.

yolo---you-only-look-once-deep-learning-model icon yolo---you-only-look-once-deep-learning-model

You Only Look Once(YOLO) is a fast, accurate object detector, making it ideal for computer vision applications. I connected YOLO to a webcam and verified that it maintains real-time performance, including the time to fetch images from the camera and display the detections. The trained data for this project was found on GitHub. The resulting system is interactive and engaging. While YOLO processes images individually, when attached to a webcam it functions like a tracking system, detecting objects as they move around and change in appearance

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