AliAmini93

AliAmini93's Stars

• AliAmini93/SAM-Breast-Tumor-Segmentation

  Developed a custom application of the Segment Anything Model (SAM) for breast cancer tissue segmentation, utilizing Hugging Face's Transformers and fine-tuning the decoder to predict segmentation masks in medical imaging.

  Language:Jupyter Notebook37201

• AliAmini93/TelecomSent

  Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom dataset. Provided actionable insights to telecom operators for customer satisfaction and competitive analysis.

  Language:Jupyter Notebook26102

• AliAmini93/WSN-Scheduling-with-Reinforcement-Learning

  Developed a reinforcement learning framework using Deep Q-Networks (DQN) to optimize scheduling in Wireless Sensor Networks (WSN), enhancing energy efficiency and state estimation through a custom simulation environment.

  Language:Jupyter Notebook24102

• AliAmini93/Telecom-Churn-Analysis

  Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights for targeted customer retention.

  Language:Jupyter Notebook22104

• AliAmini93/Bank-Marketing-Campaign-Classification

  Language:Jupyter Notebook12101

• nikhilpatil44/insurance-premium-prediction

  Build a model that estimates the cost of the premium.

  Language:Jupyter Notebook11115

• AliAmini93/Estimation-Enhancing-in-Optoelectronic-Property-Using-OIPs-and-Tight-Binding

  This MATLAB codes is used for calculating of Orbital Intraction Parameters (OIPs) in ETBM

  Language:MATLAB700

• AliAmini93/NASA-website-queries-prediction

  A hybrid approach was developed to predict NASA website queries using neural networks and metaheuristic optimization algorithms. The weights of the model was optimized using GWO, PSO, and ICA, harnessing the strengths of these algorithms to achieve remarkable results.

  Language:MATLAB710

• Econometrics-in-r/Random-parameters-ordered-regression

  R codes for random parameters (or mixed) ordered logit and ordered probit regression models

  Language:R6101

• GabrieleDG0/Conway_Game_of_Life

  Explore a project to simulate the famous Conway's cellular automata. 🐍

  Language:Python5100

• GabrieleDG0/Wolfram_Cellular_Automata

  A simulation of Wolfram's cellular automata (the Elementary Cellular Automata). 🐍

  Language:Python5100

• Econometrics-in-r/Bayesian-Count-Regression-Model

  Bayesian NB model in winBUGS

  4100

• Econometrics-in-r/Fractional-split-ordered-regression

  R codes for random parameters fractional split ordered logit and fractional split ordered probit regression models

  Language:R3100

• Ali-Hajiebrahim-Zargar/Customers_clustring

  Language:Jupyter Notebook10

• Ali-Hajiebrahim-Zargar/EffectiveMass_VS_Thickness

  This code investigate variation of effective mass by changing thickness of materials in superlattice structures based on III-V materials

  Language:MATLAB1100

• Ali-Hajiebrahim-Zargar/GUI_ETBM

  GUI For calculation of band structure based on ETBM for Zince blande materials

  Language:MATLAB1100

• Ali-Hajiebrahim-Zargar/home_price_prediction

  Language:Jupyter Notebook1100

• Ali-Hajiebrahim-Zargar/Mismatch_VS_Thickness

  This code investigate effects of variation of matrial's thicknesses on mismatch in III-V materials

  Language:MATLAB1100

• Ali-Hajiebrahim-Zargar/OIPs-Calculation

  This MATLAB codes is used for calculating of Orbital Intraction Parameters (OIPs) in ETBM

  Language:MATLAB1101

• Ali-Hajiebrahim-Zargar/Optimize-HDL-Design

  This document, which is centered on HDL optimization with a focus on power, area, timing, etc., has been authored by Ali Haji Ebrahim Zargar and will be finalized over time.

  1100

• Ali-Hajiebrahim-Zargar/Prediction-of-heart-attack

  Language:Jupyter Notebook1100

• Ali-Hajiebrahim-Zargar/Recomender_System_in_IMDB

  Language:Jupyter Notebook1100

• BarakGahtan/Image-quantiztion-using-CUDA

  In this assignment we will implement image quantization for grayscale images. This method reduces the number of colors used in an image. The algorithm we will implement works by first creating a histogram of the gray levels in the image, then using the histogram to create a map which maps each value of these levels to a new value, and finally, using this map to create the new image. We will implement quantization on MxN grayscale images, each represented as a unsigned char array of length M*N, with values in the range [0, 255], where 0 means black, and 255 means white

  Language:Cuda1100

• BehnamLatifi/Basic-Image-Processing

  Count the number of coins in an image

  Language:Python110

• BehnamLatifi/Image-Histogram

  Calculation of image Histogram by VHDL and compare with MATLAB implementation

  Language:VHDL110

• BehnamLatifi/Othello

  Implementation of Othello game with C++

  Language:C++110

• Econometrics-in-r/Bayesian-Econometrics-in-JAGS

  Bayesian regressions in JAGS

  Language:R1100

• jolares/ai-ethics-fairness-and-bias

  Sample project using IBM's AI Fairness 360 is an open source toolkit for determining, examining, and mitigating discrimination and bias in machine learning (ML) models throughout the AI application lifecycle.

  1200

• MaurizioB/KdeConnectTray

  Smartphone and tablet support for non-Kde based environments (based on KdeConnect)

  Language:Python120

• MaurizioB/pyfreopen

  A very basic Python module to redirect stderr and stdout to a file

  Language:C120