This project explores various risk measurement methods in the context of portfolio selection for stocks from Tehran’s stock market. The goal is to build efficient
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This project focuses on classifying grapevine leaves into different categories using data mining techniques. It involves data preprocessing, model training, and evaluation. Introduction The objective
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This project is a financial analysis project that explores various aspects of the stock market, including data analysis, risk assessment, portfolio optimization, and Value at
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Project Description This project focuses on implementing Q-Learning for solving pathfinding problems in grid environments. The goal is to determine and reduce the number of
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This project focuses on predicting survival on the Titanic using logistic regression. The goal is to determine whether a passenger survived or not based on
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Assignment1 Project Description This project, focuses on analyzing a dataset related to blood donation. The dataset is named “transfusion.data” and contains information about individuals’ blood
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This project implements an assembler and disassembler for Assembly64 in both Assembly and Python Languages. Assembly64 commands can be 8, 16, 32, or 64 bits
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Utilized diverse optimization methods for problem‑solving, including Genetic Algorithm and SOM for TSP, Memetic Algorithm for N Queens, Ant Colony for Assignment Problem, Simulated Annealing for Cutting Stock, and PSO for global optimum discovery
Introduction In this project, we implement a Multilayer Perceptron (MLP) neural network with weight decay regularization to solve the Fashion MNIST classification problem. The Fashion
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Note:Before compression, the file size was 31 MB, and after compression, it reduced to 10 MB. This is a Python project that demonstrates image compression
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