Amirreza Hashemi (Amirrezahmi)

Amirrezahmi

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Location:Tehran, Iran

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Amirreza Hashemi 's repositories

SelfTalker

Engage in conversation with your virtual self using AI techniques like NLP, voice cloning, and computer vision. Get accurate answers with generated keywords, phrases, images, videos. Summarization included. Synthesize voice, create talking-head video. Seek advice, career guidance, satisfy curiosity. Endless possibilities.

Language:Jupyter NotebookLicense:MITStargazers:79Issues:25Issues:1

Zozo-Assistant

Zozo Assistant is a voice-activated chatbot that performs tasks based on user commands. It utilizes speech recognition, NLP, and ML to provide interactive responses. Users can listen to music, set alarms, check the time, weather, and engage in conversations. With AI technology and voice interaction, Zozo enhances the user experience.

Language:PythonLicense:MITStargazers:58Issues:0Issues:0

Image-Decoding

Unveil hidden messages within images using Minesweeper-inspired decoding. Left-click to reveal clues, right-click to flag suspected mines. Decode correctly to reveal parts of the image. No blind flagging! Also serves as human verification.

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AudioVisual-Fusion-Suite

In this project, we transferred the target from the first video to the second one. Additionally, we altered the characteristics of the source audio to match those of the target audio. We then blended these two projects into a single project.

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bank-management

This repository contains code for a Bank Account Management System implemented in Python. The system provides functionalities for creating, updating, and managing bank accounts, as well as performing transactions and generating various statistics.

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IG-Curiosity-Analyzer

Analyze the curiosity of your Instagram followers by calculating their engagement with your stories. Identify 100% curious followers and view their profiles. Gain insights into follower engagement. Powered by instagrapi library.

Language:Jupyter NotebookLicense:MITStargazers:15Issues:0Issues:0

Mathematica-Wolfram-notebooks

This repository houses five notebooks containing Mathematica Wolfram commands along with their detailed descriptions in Persian. Explore calculus, linear algebra, plotting, and more in the realm of mathematics through these comprehensive notebooks. Enhance your understanding and proficiency in Mathematica Wolfram with this invaluable resource.

Language:MathematicaLicense:MITStargazers:14Issues:0Issues:0

CS-Course-Chronicles

CS Course Chronicles is a GitHub repository that documents my academic progress in computer science courses during my university studies. It serves as a central hub for organizing and sharing course materials, such as lecture notes, assignments, projects, and insightful writings.

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Hashtag-Analyzer

This project analyzes tweets, extracting insights on a specific hashtag. It finds common words in hashtag-containing tweets and lists accounts using the hashtag. It employs NLTK library for text processing.

Language:Jupyter NotebookLicense:MITStargazers:11Issues:0Issues:0

data-collector

Data Collector is an Android app that simplifies data collection and management. Easily enter questions and answers, maintain a dataset, play music, and more. Secure the dataset with a password, share it, or clear it when needed. Enjoy a user-friendly interface for efficient data organization and analysis.

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Optimize-graph-using-linked-list

Graph algorithms solve problems on graphs: collections of nodes connected by edges. They find paths, spanning trees, and detect cycles. Kruskal's algorithm finds the minimum spanning tree. It sorts edges by weight, adds them to the tree while avoiding cycles. We optimize by using linked-list-based adjacency lists.

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Code-Comparison-Tutorial

This project contains a tutorial code that helps you compare two codes and identify the differences between them. By using this code, you can compare a candidate code with a correct code and document the discrepancies. Additionally, the code also prints the line numbers and any whitespace differences between the codes.

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Breast-Cancer-Data-Analysis

We will conduct a comprehensive analysis of the dataset, focusing on identifying key features that influence outcomes. To achieve this, we will employ Logistic Regression and TabNet models to discern feature importance.

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