Abdul Mohiz (AMevans12)

AMevans12

Geek Repo

Location: Rawalpindi, Pakistan

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Abdul Mohiz's starred repositories

machine_learning_examples

A collection of machine learning examples and tutorials.

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CliffNotes-AI

This repository contains a Streamlit application for text summarization using transformer models. The app supports summarizing text from user inputs and uploaded files, featuring session management and clipboard copying functionality.

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CS50-AI-Language-ps6

This repository contains projects from Week 6 of the CS50 AI course, focusing on language processing. It includes the Parser project, which involves natural language parsing, and the Attention project, which explores attention mechanisms in neural networks.

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CS50-AI-NeuralNetworks-ps5

This repository contains the Traffic project from the neural networks week of the CS50 AI course. The project involves using convolutional neural networks (CNNs) to classify images of traffic signs accurately. Developed as part of the course to demonstrate the application of deep learning in computer vision tasks.

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CS50-AI-Learning-ps4

This repository contains projects from Week 4 of the CS50 AI course, focusing on machine learning. It includes the Shopping project, which uses ML algorithms for prediction, and the Nim game, showcasing reinforcement learning techniques.

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CS50-AI-Optimization-ps3

A project focused on solving a crossword puzzle using optimization techniques. It utilizes constraint satisfaction and backtracking algorithms to efficiently fill in the puzzle. Developed as part of the CS50 AI course.

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CS50P-Final-Project

A Python-based random password generator designed for enhanced security. It creates strong, unique passwords by combining letters, numbers, and special characters. Ideal for personal and professional use.

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CS50-AI-Uncertainity-ps2

Solutions for CS50 AI Week 2: Heridity and PageRank problems. Includes implementations of a Bayesian network for genetic trait prediction and the PageRank algorithm for ranking web pages.

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CS50-AI-Knowledge-ps1

This repository contains solutions for Week 1 of Harvard’s CS50 AI course. It features two projects: Knights, a logic puzzle solving truth-tellers and liars, and Minesweeper, an AI-driven implementation of the classic game using logical inference techniques.

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DEP

This repository contains all the work and projects developed during my internship at DEP. It includes code, documentation, and relevant resources for easy sharing and collaboration.

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Quantum-Codes-Qiskit-Module-

Explore quantum computing with Qiskit! Dive into Grover's algorithm, Quantum Fourier Transform, and more. Includes code executed on IBM Quantum Experience.

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Machine-Learning

A collection of basic machine learning and deep learning codes, designed to provide a foundational understanding of these fields. This repository includes simple, well-commented examples of core concepts and algorithms, covering data preprocessing, model implementation, and evaluation.

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Python-projects

Hey there! Welcome to my Python Projects repository! I'm an undergraduate student, and this is where I store all the cool stuff I've been working on for my semester projects. From fun little scripts to some more serious applications, you'll find a bit of everything here. Happy coding!

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CS50-AI-Search-ps0

Problem Set 0: Degrees of Separation & Tic-Tac-Toe This repository contains solutions for CS50 AI's Problem Set 0: Degrees of Separation: Find the shortest path between two actors via co-stars using a breadth-first search algorithm. AI Tic-Tac-Toe: An AI Tic-Tac-Toe game using the Minimax algorithm to ensure the AI never loses.

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CS50p-Codes

Welcome to my CS50P repository! This collection showcases my solutions to the problem sets from Harvard's CS50P course, which offers a comprehensive introduction to programming using Python. Each problem set covers fundamental and advanced programming concepts, designed to build a solid foundation in Python.

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Deep-Learning

This repository contains a variety of deep learning models and tools for different applications, such as image and text processing. It provides comprehensive examples, clear documentation, and utility scripts to streamline your deep learning workflow and enhance model development and experimentation.

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