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MahanVeisi8/README.md

Welcome to My GitHub Profile!

πŸ‘¨β€πŸ’» About Me

I'm Mahan Veisi, a passionate computer engineer with a keen interest in Reinforcement Learning (RL), Computer Vision, and Generative AI. Currently, I'm pursuing my Bachelor's in Computer Engineering at Shahid Beheshti University, Tehran. My journey in tech is fueled by curiosity and a desire to push the boundaries of what AI can achieve.

Trophies

  • πŸ”­ Currently working on: Generative Adversarial Networks(GAN).
  • 🌱 Exploring: Advanced Reinforcement Learning techniques and their applications in robotics and game theory.
  • ⚑ Looking to collaborate on: Open-source AI projects, particularly in RL and computer vision.

πŸ“ˆ GitHub Stats

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πŸ”— Connect with Me

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πŸš€ My Technical Arsenal

Python Solidity C++ Java MATLAB SQL Flutter

PyTorch TensorFlow Keras NumPy Pandas Scikit-Learn Pillow OpenCV

Django Flask Git MySQL

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  1. Automated-readme-generator-with-Multi-Agent-CrewAI Automated-readme-generator-with-Multi-Agent-CrewAI Public

    Fully automated README.md generator powered by multi-agent CREW AI πŸ€– and Llama3-70B πŸ§ β€”analyzing project structure πŸ“‚ and creating custom README styles ✨!

    Jupyter Notebook 9

  2. RL_practices RL_practices Public

    Collection of my Reinforcement Learning (RL) practices including DQN, D3QN, and Adaptive Gamma, applied to the Lunar Lander and CartPole environments. πŸš€πŸ•ΉοΈ

    Jupyter Notebook 10

  3. Face_recognition Face_recognition Public

    A Flask-based celebrity face recognition system using an ensemble model built with TensorFlow to classify images of Iranian celebrities

    Jupyter Notebook 11

  4. FashionTagger FashionTagger Public

    Upload your fashion images and get detailed labels, such as category, color, and season, predicted by my AI model using an ensemble of CNN architectures.

    Jupyter Notebook 9

  5. MLPractices MLPractices Public

    A collection of machine learning practices covering decision trees, KNN, stroke prediction, neural networks, DBSCAN clustering, and more

    Jupyter Notebook 9

  6. Readahead-Optimization-Using-ML-Models Readahead-Optimization-Using-ML-Models Public

    Implements Decision Trees, Neural Networks, and Random Forests to optimize the Readahead feature in Linux. Includes data preprocessing, feature selection, and model training for dynamic workload cl…

    Jupyter Notebook 4