Alireza Parvaresh's repositories
spotify-recommendation-system
Cosine similarity is one of the most widely used and powerful similarity measure in Data Science. It is used in multiple applications such as finding similar documents in NLP, information retrieval, finding similar sequence to a DNA in bioinformatics, detecting plagiarism and may more.
Evaluation-of-machine-translation-by-NLP
To evaluate machine translation, they use several methods, some of which we fully implemented
ML-algorithms-from-Scratch
Here we have fully implemented a number of algorithms related to machine learning
NLP-Projects
This repository contains a collection of Natural Language Processing (NLP) projects
web-scraper-projects
This repository contains projects that include web scraping
evaluator-targoman
We at the Telecommunication Research Center decided to test and evaluate the Tergoman machine translation system. This evaluation is done by 6 algorithms
Game-with-csp
This Python script provides a Sudoku solver using the Constraint Satisfaction Problem (CSP) algorithm. It is implemented with a modular structure, including classes for CSP, a set of CSP for Sudoku, and a class for managing the Sudoku board game.
Tehran-House-Price-Prediction
Prediction of house prices in Tehran by machine learning algorithms
Credit-Card-Fraud-Detection
The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:
Url-shorter-with-Flask
This Python script allows you to download images from Google Images based on a specified search term. It uses Selenium to automate the process of searching for images, clicking on them to reveal the full-size image, and then downloading those images to a specified folder.
Satellite-data
This repository provides Python code for converting satellite data into a format suitable for deep learning models. It supports various deep learning architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory networks (LSTMs).
clustering-with-genetic
This Python script implements a genetic algorithm for clustering data. The algorithm optimizes the cluster assignments of data points using a genetic approach, aiming to improve the silhouette score. The silhouette score is a measure of how well-defined the clusters are in the data.
parvvaresh
Config files for my GitHub profile.
pacman-with-MIN-MAX
A Pacman game implementation with an AI player using the Minimax algorithm. This project showcases the classic Pacman game environment, where the player (Pacman) navigates a maze to collect points while avoiding ghosts. The AI-controlled ghosts aim to catch Pacman.
resume-classification
We categorize resumes using machine learning algorithms and vectorizing sentences
Genetic-Algorithm-for-String-Guessing
This project implements a genetic algorithm to guess a target string. The algorithm evolves a population of candidate strings over multiple generations, aiming to converge to the specified target.
University-food-system-database-design
This is a project for the database design course at Amirkabir University of Technology
Iranian-news-dataset
This project focuses on data extraction of Persian news articles from the Fars News website. The extracted data can be utilized for various purposes, particularly in the field of artificial intelligence research at the Telecommunications Research Center.
aStar-algorithm
The A* algorithm combines the actual cost (g), which represents the distance traveled, with a heuristic cost (h) that estimates the remaining distance to the goal. It intelligently selects the most promising nodes to explore, leading to efficient pathfinding in search spaces.
download-manager
This is a simple Python script that allows you to download a file from a URL in multiple parts concurrently, merge them, and save the complete file locally. This can be useful when downloading large files, as it allows for faster downloads by utilizing multiple connections.
parvvaresh.github.io
personal websit
practice-pandas
Some questions and answers about Pandas