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P-Darabi/README.md

Hey Data Dreamers!!

🚀 Data is God in the world of Machine Learning! Ready to dive into a world where data reigns supreme? Let's make magic together!

I am a Computer Vision Researcher and Machine Learning Specialist passionate about leveraging advanced algorithms to solve real-world challenges. I strive to contribute to the data science community by sharing knowledge, collaborating on innovative projects, and fostering collective growth.

Let’s connect, learn, and work towards impactful AI-driven solutions together!

Core Skills:

  • 🐍 Programming Languages: Python
  • 🎛️ Databases: SQL Server| MongoDB
  • 🤖 Machine Learning: Supervised Learning| Unsupervised Learning| Gradient Boosting| Ensemble learning| Model Evaluation| Validation
  • 🛠️ Feature Engineering: Feature Selection| Feature Extraction| Dimensionality Reduction| Imputation| Scaling| Encoding
  • 📊 Data Manipulation & Analysis: Pandas| NumPy| Data Cleaning| Exploratory Data Analysis
  • 📈 Data Visualization: Matplotlib| Seaborn
  • 🧠 Deep Learning: TensorFlow| PyTorch| Convolutional Neural Networks (CNN)| You Only Look Once (YOLO)| Auto Encoder| Self-Organising Map (SOM)
  • 📸 Computer Vision: Image Classification| Object Recognition| Image Processing| OpenCV| Object Detection| Object Segmentation| Object Tracking| Facial Recognition
  • 🌀 Version Control: GitHub

Projects

The following are some of the notable data science projects I have worked on. Each project showcases my skills in data analysis, machine learning model development, and insights extraction.

Classification Models

💡Diagnosis Diabetic Retinopathy (PyTorch)

  • Description: Using Convolutional Neural Network for Diabetic Retinopathy Detection
  • Technologies: Convolutional Neural Network, Pytorch, OOP
  • GitHub Repository: Diagnosis of Diabetic Retinopathy

💡Detection Brain Tumor (PyTorch)

  • Description: Using Convolutional Neural Network for Brain Tumor Detection and Diagnosis (F1-score: 0.97)
  • Technologies: Convolutional Neural Network, Pytorch, OOP
  • GitHub Repository: Brain Tumor Detection

💡Pneumonia Diagnosis (Transfer Learning)

💡Ticket Cancellation Prediction (XGBoost Classifier)

  • Description: This project aims to develop a model that accurately predicts whether users will cancel their tickets. Each cancellation incurs a fine for the ticket registration site from the passenger company
  • Technologies: Sklearn, Xgboost, GridSearchCV, ...
  • GitHub Repository: Prediction Of Ticket Cancellation by XGBoost Classifier

💡Category Prediction in an Advertisement Website

  • Description: Category Prediction in an Advertisement Website
  • Technologies: Sklearn, GridSearchCV, SVM, RandomForest, XGBoost, Sklearn.metrics, Textual Vectorization, TF-IDF vectorization
  • GitHub Repository: Category-Prediction-in-an-Advertisement-Website

💡Detection of Type-2 Diabetes Mellitus Disease

  • Description: XGBoost and CatBoost are powerful machine-learning models that can be used to predict diabetes
  • Technologies: Sklearn, Xgboost, Catboost, GridSearchCV, ...
  • GitHub Repository: Prediction Of Diabetes XGBoost CatBoost

💡Analyzing Previous Marketing Campaign Patterns

  • Description: Analysis of Bank Marketing Strategies for Future Success
  • Technologies: Sklearn, Numpy, Pandas, Matplotlib, Seaborn, GridSearchCV, Ensemble, Sklearn.metrics
  • GitHub Repository: [Bank Marketing Strategies for Future Success

Predictive model

💡Predict the Price Of Diamond (Regression Models)

  • Description: My primary objective in this problem is to accurately predict the price of diamonds by analyzing a comprehensive set of their defining characteristics
  • Technologies: Sklearn, Numpy, Pandas, Matplotlib, Seaborn, GridSearchCV, Linear_model, Ensemble, Sklearn.metrics
  • GitHub Repository: Predict Price Of Diamond By Regression Models

Object Detection & Tracking

💡YOLOv8 Signs Detection

  • Description: YOLOv8-Based Traffic Signs Detection Model|Training Using Customized Dataset Of Traffic Signs
  • Technologies: YOLOv8, PyTorch
  • GitHub Repository: Traffic Signs Detection YOLOv8

💡YOLOv8 Car Tracking

Generative AI

💡Generating Anime Faces

  • Description: The project has successfully generated compelling anime faces that showcase the realism achieved with DCGAN
  • Technologies: TensorFlow, DCGAN
  • GitHub Repository: Generating Anime Faces (DCGAN)

Data Preprocessing

💡Data Preprocessing For Machine Learning

  • Description: Pre-processing Data: A Step-by-Step Guide and Professional Approach using Class Definition
  • Technologies: OOP, Sklearnlearn, Feature Engineering, Feature selection
  • In Kaggle: Data Preprocessing For Machine Learning)

Object segmentation

💡Medical Image Segmentation (kidney Tumor)

Get in Touch

If you have inquiries, or collaboration opportunities, or wish to delve into discussions regarding data science projects, please don't hesitate to get in touch. I welcome your outreach and can be reached via email or connect with me on LinkedIn.

Pinned Loading

  1. Generating-Anime-Faces-with-DCGAN Generating-Anime-Faces-with-DCGAN Public

    Generating Anime Faces with DCGAN: A Dataset of High-Quality Anime

    Jupyter Notebook 2

  2. Traffic-Signs-Detection-By-YOLOv8 Traffic-Signs-Detection-By-YOLOv8 Public

    Traffic-Signs-Detection-By-YOLOv8

    Jupyter Notebook 7

  3. Brain-Tumor-Detection Brain-Tumor-Detection Public

    Convolutional Neural Network for Brain Tumor Detection and Diagnosis (Pytorch, F1-score: 0.97)

    Jupyter Notebook 7 2

  4. Diagnosis_Of_Pneumonia_By_CNN_Classifier Diagnosis_Of_Pneumonia_By_CNN_Classifier Public

    😊🎉ConvolutionalNeuralNetwork😊🎉In this repository, I will demonstrate the progress of an image classification project that aims to distinguish between healthy individuals and those with pneumonia.

    Jupyter Notebook 1

  5. Prediction_Of_Ticket_Cancellation_Acc_98 Prediction_Of_Ticket_Cancellation_Acc_98 Public

    😊🎉Prediction Of Ticket Cancellation by XGBoost Classifier😊🎉

    Jupyter Notebook 2

  6. Text_Classification_By_SVM Text_Classification_By_SVM Public

    Text Classification for Category Prediction using SVM, RandomForest, and XGBoost classifier: A Case Study with Yektanet Dataset

    Jupyter Notebook 1