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  • Tehran
  • 10:16 (UTC +03:30)

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Achievement: Pull SharkAchievement: Quickdraw

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Achievement: Pull SharkAchievement: Quickdraw

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MiladBadeleh/README.md

Hi, I'm Milad Badeleh


💻 Tech Stack:

👉 Programming languages

Python C++ C AssemblyScript R

👉 Machine Learning & Deep Learning

TensorFlow PyTorch Pandas scikit-learn NumPy Keras

👉 FRAMEWORKS, PLATFORMS & LIBRARIES

WordPress

👉 Cloud Hosting

AWS Azure Cloudflare Google Cloud Linode Heroku DigitalOcean

👉 Databases

MySQL Postgres MongoDB MariaDB

👉 Software & Tools

Power Bi Postman TOR Jira Kubernetes nVIDIA

👉 Version Control

Git GitHub GitLab

👉 Servers

Apache Nginx

👉 Others

Arduino Raspberry Pi

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  1. Concrete-Crack-Detection-Using-DenseNet121 Concrete-Crack-Detection-Using-DenseNet121 Public

    This project implements a DenseNet121 model for concrete crack classification using PyTorch. The model is trained on a custom dataset, with images resized to 224x224 and normalized using ImageNet's…

    Jupyter Notebook 1

  2. Concrete-Crack-Detection-Using-ResNet18 Concrete-Crack-Detection-Using-ResNet18 Public

    This project implements a ResNet18 model for concrete crack classification using PyTorch. The model is trained on a custom dataset, with images resized to 224x224 and normalized using ImageNet's me…

    Jupyter Notebook 1

  3. Concrete-Crack-Detection-Using-ResNet50 Concrete-Crack-Detection-Using-ResNet50 Public

    This project implements a ResNet50 model for concrete crack classification using PyTorch. The model is trained on a custom dataset, with images resized to 224x224 and normalized using ImageNet's me…

    Jupyter Notebook 5

  4. Concrete-Crack-Detection-Using-VGG11 Concrete-Crack-Detection-Using-VGG11 Public

    This project implements a VGG11 model for concrete crack classification using PyTorch. The model is trained on a custom dataset, with images resized to 224x224 and normalized using ImageNet's mean …

    Jupyter Notebook 2