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Neural-Network-Optimized-by-PSO
this project integrates - ● Neural Network and Particle Swarm Optimization together to reduce training time of neural network. this is a fun machine learning experiment. This project analyzes the performance of NN optimized by PSO Replacing Back propagation. This hybrid approach then employed on a disease dataset and classified the diasese successfully. For comparison Purpose other well known approaches have also been implemented here in this project to compare the accuracy as well as efficiency of our model. this project has been implemented in python.Bus-reservation-system-.Net-C-
This project has been developed using C# programming language in .NET framework. For database system SQLite software has been used.Student-CGPA-Information-Management-System
This project has been implemented and developed using JAVA swing GUI toolkit and JAVA abstract window (AWT) toolkit to manupulate and process information regarding university students. for database manupulation purpose MySql has been considered for this project.Uber-Taxi-transportation-system
Hierarchical-Design-of-16-Bit-ALU
this project implements 16 bit ALU using verilog programming.Multithreaded-WebServer
This project implements multithreaded webserver using the concept of socket programming and concept of threadpool to negotiate with concurrent requests at a specific time using c programming.Python-Web-Scrapping-Selenium-beautifulSoup
This is a data extraction and analysis project which has been done on hundreds of japaneese hospital to extract their job circular information and further processing them to get meaningful information. The overall implementation has been done using python Selenium and beautifulSoup library which are considered best libraries for scrapping data from web.Neural-Network-Optimized-by-ACO
# Neural-Network-Optimized-by-ACO this project integrates - ● Neural Network and Ant Colony Optimization (ACO) together to reduce training time of neural network. this is a fun machine learning experiment. This project analyzes the performance of NN optimized by ACO Replacing Back propagation. This hybrid approach then employed on a disease dataset and classified the diasese successfully. For comparison Purpose other well known approaches have also been implemented here in this project to compare the accuracy as well as efficiency of our model. this project has been implemented in JAVA.Love Open Source and this site? Check out how you can help us